{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Populating the interactive namespace from numpy and matplotlib\n" ] } ], "source": [ "import os\n", "import re\n", "import sys\n", "import dataset\n", "import json\n", "import inspect\n", "from copy import deepcopy\n", "from dimerAtomMethods import *\n", "from miscMethods import au2A\n", "from scipy.optimize import curve_fit\n", "%pylab inline\n", "\n", "import random" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": true }, "outputs": [], "source": [ "def au2kcal(x):\n", " if type(x) is not list: \n", " x = [ x ]\n", " islist=0\n", " if x==[None]:\n", " return None\n", " else:\n", " islist=1\n", " for i in range(len(x)):\n", " x[i]=x[i]*627.50960803\n", " if not islist:\n", " x=x[0]\n", " return x" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": true }, "outputs": [], "source": [ "jobDB='jobDB.db'" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false }, "outputs": [], "source": [ "positionsDict={}\n", "positionsDict['asymt']=[]\n", "positionsDict['asymt'].append({\"atom\":'Cu', \"position\":[ 0.000000000, 0.000000000, 0.000000000]})\n", "positionsDict['asymt'].append({\"atom\":'Cu', \"position\":[ 2.552655436, 0.000000000, 0.000000000]})\n", "positionsDict['asymt'].append({\"atom\":'Cu', \"position\":[ -1.276327718, 2.210664573, 0.000000000]})\n", "positionsDict['asymt'].append({\"atom\":'Cu', \"position\":[ 1.276327718, 2.210664573, 0.000000000]})\n", "positionsDict['asymt'].append({\"atom\":'Cu', \"position\":[ 1.276327756, 0.736888213, -2.063000000]})\n", "positionsDict['asymt'].append({\"atom\":'Cu', \"position\":[ 3.828983193, 0.736888213, -2.063000000]})\n", "positionsDict['asymt'].append({\"atom\":'Cu', \"position\":[ 0.000000038, 2.947552786, -2.063000000]})\n", "positionsDict['asymt'].append({\"atom\":'Cu', \"position\":[ 2.552655474, 2.947552786, -2.063000000]})\n", "positionsDict['asymt'].append({\"atom\":'Cu', \"position\":[ 0.000000000, 1.473776426, -4.143000000]})\n", "positionsDict['asymt'].append({\"atom\":'Cu', \"position\":[ 2.552655436, 1.473776426, -4.143000000]})\n", "positionsDict['asymt'].append({\"atom\":'Cu', \"position\":[ -1.276327718, 3.684440999, -4.143000000]})\n", "positionsDict['asymt'].append({\"atom\":'Cu', \"position\":[ 1.276327718, 3.684440999, -4.143000000]})\n", "positionsDict['asymt'].append({\"atom\":'Cu', \"position\":[ 0.000000000, 0.000000000, -6.227000000]})\n", "positionsDict['asymt'].append({\"atom\":'Cu', \"position\":[ 2.552655436, 0.000000000, -6.227000000]})\n", "positionsDict['asymt'].append({\"atom\":'Cu', \"position\":[ -1.276327718, 2.210664573, -6.227000000]})\n", "positionsDict['asymt'].append({\"atom\":'Cu', \"position\":[ 1.276327718, 2.210664573, -6.227000000]})\n", "positionsDict['ts']=deepcopy(positionsDict['asymt'])\n", "positionsDict['asymt'].append({\"atom\":'H', \"position\":[ 1.276327702, .370720000, 6.499999984]})\n", "positionsDict['asymt'].append({\"atom\":'H', \"position\":[ 1.276327735, -.370720000, 6.500000016]})\n", "positionsDict['ts'].append({\"atom\":'H', \"position\":[ 1.276327696, 0.516000000, 1.163999977]})\n", "positionsDict['ts'].append({\"atom\":'H', \"position\":[ 1.276327741, -0.516000000, 1.164000023]})\n", "\n", "v1=[ 5.105310873, 0.000000000, 0.000000000]\n", "v2=[-2.552655436, 4.421329147, 0.000000000]\n", "v3=[ 0.000000000, 0.000000000, 19.227000000]\n", "\n", "PPm='myPPs_V01'\n", "PPj='jorg'\n", "\n", "#shift atom into center of simulation cell in z direction (according to asymt geometry) \n", "z=[]\n", "for atom in positionsDict['asymt']:\n", " z.append(atom['position'][2])\n", "shiftz=v3[2]/2-(min(z)+max(z))/2\n", "for geom in ['asymt', 'ts']:\n", " for atom in positionsDict[geom]:\n", " atom['position'][2]=atom['position'][2]+shiftz\n" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": true }, "outputs": [], "source": [ "jobRecord0={}\n", "\n", "jobRecord0['convThrs']=1.0E-16\n", "jobRecord0['bravLatt']='free'\n", "jobRecord0['celldm1']=None\n", "jobRecord0['v1']=json.dumps(v1)\n", "jobRecord0['v2']=json.dumps(v2)\n", "jobRecord0['v3']=json.dumps(v3)\n", "homedir=\"/nfs/home1/kdd/Project_H2onCu111/runs_singePrecBlip_convThrs1E-16/\"\n", "jobRecord0['ppdirUpf']=homedir+'Pseudopotentials/pwscf'\n", "jobRecord0['ppList']=json.dumps([PPm]*4+[PPj]*14)\n", "jobRecord0['ecut']=350\n", "jobRecord0['nkz']=1\n", "jobRecord0['ksz']=0.0\n", "jobRecord0['smearingTyp']='marzari-vanderbilt'\n", "jobRecord0['smearingVal']=0.0074\n", "jobRecord0['blipMult']=2.5\n", "jobRecord0['blipSinglePrec']='T'" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": false }, "outputs": [], "source": [ "def getStandardDFTentry(geom, nkx, nky, iks, changeDict={}):\n", " #use iks=-1 for gamma point\n", " if nkx==1 and nky==1 and not iks==-1:\n", " random.seed(1233.1236)\n", " ksx=[]\n", " ksy=[]\n", " for ikPoint in range(12):\n", " ksx.append(random.random())\n", " ksy.append(random.random())\n", " elif nkx==2 and nky==2 and not iks==-1:\n", " ksy=[0.0,0.0,0.0,0.125,0.125,0.125,0.25]\n", " ksx=[0.0,0.125,0.25,-0.25,0.0,0.125,0.0]\n", " weight=[1.0, 4.0, 2.0, 2.0, 2.0, 4.0, 1.0]\n", " elif iks==-1:\n", " ksx=[0]\n", " ksy=[0]\n", " else:\n", " sys.exit(\"Have no definition of ks for supercelss other than kx=0, ky=0\")\n", " jobRecord=deepcopy(jobRecord0)\n", " jobRecord['executingProgram']='pwscfCrystal'\n", " jobRecord['geom']=dict2xyz(positionsDict[geom])\n", " jobRecord['xc']=None\n", " jobRecord['nkx']=nkx\n", " jobRecord['nky']=nky\n", " jobRecord['ksx']=ksx[iks]\n", " jobRecord['ksy']=ksy[iks]\n", " if nkx==2 and nky==2 and not iks==1:\n", " jobRecord['weight']=weight[iks]\n", " jobRecord.update(changeDict)\n", " if jobRecord['executingProgram']=='pwscfCrystalNoCasino': #drop all irrelevant fields\n", " del jobRecord['blipSinglePrec']\n", " del jobRecord['blipMult']\n", " return jobRecord\n", " " ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": false }, "outputs": [], "source": [ "def getStandardDMCentry(geom, nkx, nky, iks, dt, changeDict={}):\n", " \n", " jobRecord=getStandardDFTentry(geom, nkx, nky, iks)\n", " #find orbital from \n", " with dataset.connect('sqlite:///'+jobDB) as DBdata:\n", " jobFromsOrb=list(DBdata['data'].find(**jobRecord))\n", " if not len(jobFromsOrb)==1:\n", " for job in jobFromsOrb:\n", " print job\n", " print jobRecord\n", " sys.exit(\"Found no or more than one orb directories\")\n", " \n", " jobRecord['executingProgram']='casino'\n", " \n", " #find decorr from\n", " jobRecordFrom=deepcopy(jobRecord)\n", " jobRecordFrom['qmctyp']='vmc'\n", " jobRecordFrom['ksx']=0.0 #use gamma point calc to testimate decorr \n", " jobRecordFrom['ksy']=0.0\n", " jobRecordFrom['nkx']=1 #use smallest supercell to estimate decorr\n", " jobRecordFrom['nky']=1\n", " if 'weight' in jobRecordFrom:\n", " del jobRecordFrom['weight']\n", " del jobRecordFrom['convThrs']#do not care about convThrs for decorr length\n", " with dataset.connect('sqlite:///'+jobDB) as DBdata:\n", " jobFromsDecorr=list(DBdata['data'].find(**jobRecordFrom))\n", " if not len(jobFromsDecorr)==1:\n", " for job in jobFromsDecorr:\n", " print job\n", " print jobRecordFrom\n", " sys.exit(\"Found no or more than one decorr directories\")\n", " \n", " #define Jastrow\n", " jobRecord['jastrowList']=json.dumps([[1,2,3,4],[5,6,7,8,9,10,11,12,13,14,15,16],[17\\\n", ",18]])\n", " jobRecord['Nu']=5\n", " jobRecord['Nchi']=json.dumps([5,5,5])\n", " jobRecord['Nf']=json.dumps([2,2,2])\n", " jobRecord['spinDepUChiF']=json.dumps([1,1,0])\n", " \n", " jobRecord.update(changeDict)\n", " \n", " #find JastrowFrom\n", " jobRecordFrom=deepcopy(jobRecord)\n", " jobRecordFrom['qmctyp']='emin'\n", " jobRecordFrom['ksx']=0.0 #use gamma point calc for optimized Jastrow \n", " jobRecordFrom['ksy']=0.0\n", " if 'weight' in jobRecordFrom: #do not care about weight factoe\n", " del jobRecordFrom['weight']\n", " del jobRecordFrom['convThrs'] #do not care about the convergence threshold used in pwscf of the optimized Jastrow \n", " with dataset.connect('sqlite:///'+jobDB) as DBdata:\n", " jobFromsJast=list(DBdata['data'].find(**jobRecordFrom))\n", " if not len(jobFromsJast)==1:\n", " sys.exit(\"Found no or more than one jast directories\")\n", " \n", " \n", " jobRecord['decorrFrom']=jobFromsDecorr[0]['id']\n", " jobRecord['orbitalsFrom']=jobFromsOrb[0]['id']\n", " jobRecord['jastrowFrom']=jobFromsJast[0]['id']\n", " \n", " jobRecord['qmctyp']='vmc_dmc'\n", " homedir=\"/nfs/home1/kdd/Project_H2onCu111/runs_singePrecBlip_convThrs1E-16/\"\n", " jobRecord['ppdirCasino']=homedir+'Pseudopotentials/casino'\n", " \n", " jobRecord['interaction']='ewald'\n", " jobRecord['expval_cutoff']=0\n", " \n", " jobRecord['vmc_equil_nstep']=10000 #estimated from lamda=12A=24au and N=lamda^2/(2*dim*\\D*tau*accept)~1000 (with D=1/2 for electrons)\n", " jobRecord['decorrFactor']=4\n", " if jobRecord['nkx']==1 and jobRecord['nky']==1:\n", " jobRecord['vmc_nconfig_write']=12288\n", " else:\n", " jobRecord['vmc_nconfig_write']=6048\n", " jobRecord['dt']=dt\n", " jobRecord['tmove']='T'\n", " jobRecord['jastrowFromChoose']='lowestEnergy'\n", " \n", " jobRecord.update(changeDict) #put this in again in case we want to override the normal jastrowFrom etc\n", " \n", " return jobRecord" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "collapsed": false }, "outputs": [], "source": [ "def getResult(method,geom, nkx, nky, iks, dt, changeDict={}):\n", " if method=='DFT':\n", " jobRecord=getStandardDFTentry(geom, nkx, nky, iks, changeDict)\n", " elif method=='DMC':\n", " jobRecord=getStandardDMCentry(geom, nkx, nky, iks, dt, changeDict)\n", " else:\n", " sys.exit(\"Unknown method.\")\n", " with dataset.connect('sqlite:///'+jobDB) as DBdata:\n", " results=list(DBdata['data'].find(**jobRecord))\n", " \n", " if len(results)==0:\n", " print jobRecord\n", " sys.exit(\"Found no DB entry\")\n", " elif len(results)>1:\n", " sys.exit(\"Found more than 1 DB entry\")\n", " \n", " return results[0]" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "collapsed": false }, "outputs": [], "source": [ "def getNumber(number,method='', geom='', nkx=0, nky=0, iks=-2, dt=-0.1, changeDict={}, inDict={}):\n", " if inDict=={}:\n", " resultDict=getResult(method, geom,nkx,nky,iks, dt, changeDict)\n", " else:\n", " resultDict=inDict\n", " resultStr=resultDict[number]\n", " try:\n", " result=float(resultStr)\n", " except:\n", " result=float('NaN')\n", " \n", " if number=='CorrelCorrError':\n", " resError=getNumber('ErrorInCorrelCorrError', inDict=resultDict)\n", " #if resError/result>0.1:\n", " # result=float('Inf')\n", " \n", " return result" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "collapsed": false }, "outputs": [], "source": [ "class results():\n", " def __init__(self,method, nkx, nky, iks, dt, changeDict={}):\n", " #check which input arguments will determine the array in results\n", " frame = inspect.currentframe()\n", " args, _, _, values = inspect.getargvalues(frame)\n", " argLen=np.zeros(len(args))\n", " for i in range(1,len(args)):\n", " try:\n", " argLen[i]=len(values[args[i]])\n", " if isinstance(values[args[i]], str) or isinstance(values[args[i]],dict):\n", " argLen[i]=1\n", " except:\n", " argLen[i]=1\n", " if not all(x==argLen[argLen>1][0] for x in argLen[argLen>1]):\n", " sys.exit(\"Something weird with input!\")\n", " self._length=int(max(argLen))\n", " for i in range(1,len(args)):\n", " if argLen[i]==1:\n", " values[args[i]]=[values[args[i]]]*self._length\n", " \n", " self._recordsAsymt=[]\n", " self._recordsTs=[]\n", " for i in range(self._length):\n", " self._recordsAsymt.append(getResult(values[args[1]][i],'asymt', values[args[2]][i], values[args[3]][i], values[args[4]][i], values[args[5]][i], values[args[6]][i]))\n", " self._recordsTs.append(getResult(values[args[1]][i],'ts', values[args[2]][i], values[args[3]][i], values[args[4]][i], values[args[5]][i], values[args[6]][i]))\n", " \n", " def tsEnergy(self):\n", " en=np.zeros(self._length)\n", " for i in range(self._length):\n", " en[i]=au2kcal(getNumber('energy', inDict=self._recordsTs[i]))\n", " return en\n", " \n", " def asymtEnergy(self):\n", " en=np.zeros(self._length)\n", " for i in range(self._length):\n", " en[i]=au2kcal(getNumber('energy', inDict=self._recordsAsymt[i]))\n", " return en\n", " \n", " def barrierEnergy(self):\n", " en=np.zeros(self._length)\n", " for i in range(self._length):\n", " en[i]=au2kcal(getNumber('energy', inDict=self._recordsTs[i])-getNumber('energy', inDict=self._recordsAsymt[i]))\n", " return en\n", " \n", " def tsError(self):\n", " en=np.zeros(self._length)\n", " for i in range(self._length):\n", " en[i]=au2kcal(getNumber('CorrelCorrError', inDict=self._recordsTs[i]))\n", " return en\n", " \n", " def asymtError(self):\n", " en=np.zeros(self._length)\n", " for i in range(self._length):\n", " en[i]=au2kcal(getNumber('CorrelCorrError', inDict=self._recordsAsymt[i]))\n", " return en\n", " \n", " def barrierError(self):\n", " en=np.zeros(self._length)\n", " for i in range(self._length):\n", " en[i]=au2kcal(np.sqrt(getNumber('CorrelCorrError', inDict=self._recordsTs[i])**2+getNumber('CorrelCorrError', inDict=self._recordsAsymt[i])**2))\n", " return en\n", " \n", " def tsEnergy_defEquil(self):\n", " en=np.zeros(self._length)\n", " for i in range(self._length):\n", " en[i]=au2kcal(getNumber('energy_defEquil', inDict=self._recordsTs[i]))\n", " return en\n", " \n", " def asymtEnergy_defEquil(self):\n", " en=np.zeros(self._length)\n", " for i in range(self._length):\n", " en[i]=au2kcal(getNumber('energy_defEquil', inDict=self._recordsAsymt[i]))\n", " return en\n", " \n", " def barrierEnergy_defEquil(self):\n", " en=np.zeros(self._length)\n", " for i in range(self._length):\n", " en[i]=au2kcal(getNumber('energy_defEquil', inDict=self._recordsTs[i])-getNumber('energy_defEquil', inDict=self._recordsAsymt[i]))\n", " return en\n", " \n", " def tsError_defEquil(self):\n", " en=np.zeros(self._length)\n", " for i in range(self._length):\n", " en[i]=au2kcal(getNumber('CorrelCorrError_defEquil', inDict=self._recordsTs[i]))\n", " return en\n", " \n", " def asymtError_defEquil(self):\n", " en=np.zeros(self._length)\n", " for i in range(self._length):\n", " en[i]=au2kcal(getNumber('CorrelCorrError_defEquil', inDict=self._recordsAsymt[i]))\n", " return en\n", " \n", " def barrierError_defEquil(self):\n", " en=np.zeros(self._length)\n", " for i in range(self._length):\n", " en[i]=au2kcal(np.sqrt(getNumber('CorrelCorrError_defEquil', inDict=self._recordsTs[i])**2+getNumber('CorrelCorrError_defEquil', inDict=self._recordsAsymt[i])**2))\n", " return en \n", " \n", " def weight(self):\n", " en1=np.zeros(self._length)\n", " en2=np.zeros(self._length)\n", " for i in range(self._length):\n", " en1[i]=getNumber('weight', inDict=self._recordsTs[i])\n", " en2[i]=getNumber('weight', inDict=self._recordsAsymt[i])\n", " \n", " if not all(en1==en2):\n", " print en1, en2\n", " sys.exit(\"Something wrong with weights\")\n", " return en1\n", " " ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "collapsed": true }, "outputs": [], "source": [ "def func(x, a,b):\n", " if type(x) is not list: \n", " x = [ x ]\n", " islist=0\n", " else:\n", " islist=1\n", " res=[0]*len(x)\n", " for i in range(len(x)):\n", " res[i]=a*x[i]+b\n", " if islist==0:\n", " res=res[0]\n", " return res" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "collapsed": false, "scrolled": false }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/opt/rh/python27/root/usr/lib64/python2.7/site-packages/matplotlib/collections.py:590: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n", " if self._edgecolors == str('face'):\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "a= 1.09800719714 +/- 0.271166687628\n", "b= 14.4131017944 +/- 1.87852110452\n", "\n", "method\t av. over k \t corr. from DFT \t sum \t uncert. from a \t stat. uncert.\n", "DFT\t8.19913150388 \t[ 2.15712391] \t[ 10.35625542] \t0.0 \t\t0.0\n", "DMC\t12.3967259682 \t[ 2.36853758] \t[ 14.76526355] \t[ 0.58494015] \t0.376384175\n", "[ 0.69557172]\n" ] }, { "data": { "image/png": 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fcTkH3HsAry17jUmnTGLH9jtGHUukxYt7mqqZdQYuJNiWfTvgIeAyd9c+JJKS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\nqQx7Aw/hL+8NCq4dAcypQ3sslC3FLQBG5eRamiv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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#get data DMC, DFT for smallest supercell, all k-points\n", "smallestSuperCell_DFT_ki=results('DFT', 1, 1, range(12), 0.0)\n", "smallestSuperCell_DMC_ki=results('DMC', 1, 1, range(12), 0.005)\n", "smallestSuperCell_DFT_conv=results('DFT', 16,16,-1,0.0,{'executingProgram':'pwscfCrystalNoCasino','convThrs':None})\n", "#smalleStsuperCell_DFT_conv=getNumber('energy','DFT', 'ts',16,16,-1,0.0, {'executingProgram':'pwscfCrystalNoCasino','convThrs':None})-getNumber('energy','DFT', 'asymt',16,16,-1,0.0,{'executingProgram':'pwscfCrystalNoCasino', 'convThrs':None})\n", " \n", "#plotting\n", "plt.errorbar(smallestSuperCell_DFT_ki.barrierEnergy()-smallestSuperCell_DFT_conv.barrierEnergy(),smallestSuperCell_DMC_ki.barrierEnergy(), yerr=smallestSuperCell_DMC_ki.barrierError(), fmt='o')\n", "plt.xlabel(\"barrier energy DFT(k) - DFT(k point converged)\")\n", "plt.ylabel(\"barrier energy DMC(k)[kcal/mol]\");\n", "\n", "#linear regression\n", "[popt,pcov]=curve_fit(func,smallestSuperCell_DFT_ki.barrierEnergy()-smallestSuperCell_DFT_conv.barrierEnergy(),smallestSuperCell_DMC_ki.barrierEnergy(), sigma=smallestSuperCell_DMC_ki.barrierError())\n", "[a, erra]=[popt[0], np.sqrt(np.diag(pcov))[0]]\n", "[b, errb]=[popt[1], np.sqrt(np.diag(pcov))[1]]\n", "ax=plt.gca()\n", "xmin, xmax = ax.get_xlim()\n", "plt.plot([xmin, xmax], [func(xmin,a,b), func(xmax,a,b)], '--');\n", "plt.savefig(\"kpoints2x2.svg\")\n", "print 'a=',a,'+/-',erra\n", "print 'b=',b,'+/-',errb\n", "print\n", "\n", "#means and corrections over k-points for DFT, DMC, smallest supercell\n", "#correction for DMC scaled by factor a from linear regression\n", "dftNoCorr=mean(smallestSuperCell_DFT_ki.barrierEnergy())\n", "dmcNoCorr=mean(smallestSuperCell_DMC_ki.barrierEnergy())\n", "corrDft=smallestSuperCell_DFT_conv.barrierEnergy()-mean(smallestSuperCell_DFT_ki.barrierEnergy())\n", "corrDmc=corrDft*a\n", "errCorrDmc=corrDmc*erra/a\n", "statErrDmc=np.sqrt(sum(smallestSuperCell_DMC_ki.barrierError()**2))/len(smallestSuperCell_DFT_ki.barrierEnergy())\n", "print 'method\\t av. over k \\t corr. from DFT \\t sum \\t uncert. from a \\t stat. uncert.' \n", "print 'DFT\\t', dftNoCorr, '\\t', corrDft, '\\t', dftNoCorr+corrDft, '\\t', 0.00000, '\\t\\t',0.00000 \n", "print 'DMC\\t', dmcNoCorr, '\\t', corrDmc, '\\t', dmcNoCorr+corrDmc, '\\t', errCorrDmc, '\\t',statErrDmc \n", "\n", "dmc2x2=dmcNoCorr+corrDmc\n", "errDmc2x2=sqrt(errCorrDmc**2+statErrDmc**2)\n", "print errDmc2x2" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "collapsed": false, "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "a= 1.0920345526 +/- 0.267235250704\n", "b= 14.3808278582 +/- 1.8488177054\n", "\n", "method\t av. over k \t corr. from DFT \t sum \t uncert. from a \t stat. uncert.\n", "DFT\t8.19913150388 \t[ 2.15712391] \t[ 10.35625542] \t0.0 \t\t0.0\n", "DMC\t12.4167525432 \t[ 2.35565385] \t[ 14.77240639] \t[ 0.57645955] \t0.379371008087\n", "[ 0.69009273]\n" ] }, { "data": { "image/png": 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Gp2QVytbK3Xm24llGzhjJ3EVzGdRrEN26dIs6lkirl1APBoCZbWVmo83sQ2AS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\nuzp773Sfn+XSLC3dO7Xj9cCRmfg/Atdmyvpetvw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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#get data DMC, DFT for smallest supercell, all k-points with defEquil\n", "\n", "#plotting\n", "plt.errorbar(smallestSuperCell_DFT_ki.barrierEnergy()-smallestSuperCell_DFT_conv.barrierEnergy(),smallestSuperCell_DMC_ki.barrierEnergy_defEquil(), yerr=smallestSuperCell_DMC_ki.barrierError_defEquil(), fmt='o')\n", "plt.xlabel(\"barrier energy DFT(k) - DFT(k point converged)\")\n", "plt.ylabel(\"barrier energy DMC(k)[kcal/mol]\");\n", "\n", "#linear regression\n", "[popt,pcov]=curve_fit(func,smallestSuperCell_DFT_ki.barrierEnergy()-smallestSuperCell_DFT_conv.barrierEnergy(),smallestSuperCell_DMC_ki.barrierEnergy_defEquil(), sigma=smallestSuperCell_DMC_ki.barrierError_defEquil())\n", "[a, erra]=[popt[0], np.sqrt(np.diag(pcov))[0]]\n", "[b, errb]=[popt[1], np.sqrt(np.diag(pcov))[1]]\n", "ax=plt.gca()\n", "xmin, xmax = ax.get_xlim()\n", "plt.plot([xmin, xmax], [func(xmin,a,b), func(xmax,a,b)], '--');\n", "plt.savefig(\"kpoints2x2.svg\")\n", "print 'a=',a,'+/-',erra\n", "print 'b=',b,'+/-',errb\n", "print\n", "\n", "#means and corrections over k-points for DFT, DMC, smallest supercell\n", "#correction for DMC scaled by factor a from linear regression\n", "dftNoCorr=mean(smallestSuperCell_DFT_ki.barrierEnergy())\n", "dmcNoCorr=mean(smallestSuperCell_DMC_ki.barrierEnergy_defEquil())\n", "corrDft=smallestSuperCell_DFT_conv.barrierEnergy()-mean(smallestSuperCell_DFT_ki.barrierEnergy())\n", "corrDmc=corrDft*a\n", "errCorrDmc=corrDmc*erra/a\n", "statErrDmc=np.sqrt(sum(smallestSuperCell_DMC_ki.barrierError_defEquil()**2))/len(smallestSuperCell_DMC_ki.barrierEnergy_defEquil())\n", "print 'method\\t av. over k \\t corr. from DFT \\t sum \\t uncert. from a \\t stat. uncert.' \n", "print 'DFT\\t', dftNoCorr, '\\t', corrDft, '\\t', dftNoCorr+corrDft, '\\t', 0.00000, '\\t\\t',0.00000 \n", "print 'DMC\\t', dmcNoCorr, '\\t', corrDmc, '\\t', dmcNoCorr+corrDmc, '\\t', errCorrDmc, '\\t',statErrDmc \n", "\n", "dmc2x2=dmcNoCorr+corrDmc\n", "errDmc2x2=sqrt(errCorrDmc**2+statErrDmc**2)\n", "print errDmc2x2" ] }, { "cell_type": "code", "execution_count": 26, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "DFT 0.0: 8.19913150388+/-nan\n", "DMC 0.005: 12.3967259682+/-0.376384175\n", "DMC 0.002: 12.2629028326+/-0.524613039957\n" ] }, { "data": { "image/png": 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kIlVi8uSLmTXrKFKpFRX9+lik1lXUUr4CjKBMvg54C/jU2wNm+wCHAQ9GE5rI2HV3d3PU\nUbNZvvx0urp+BfyCrq5fsnz56Rx11GxyuVzUIcrInQKsM7N/M7Ocmf23mV0cdVAiUtOUl0SkKqxc\neR2trUtVlBKpcBVTmDKzRWY2w8wONLMPmNk3CXbcu83dXyHoOXVN+JwPAMuB3wOro4taZGzmz19K\nNnsVMIOg/grBr+sMstklJJOp6IKT0ToYuBR4HDgGuApYYmZfiTQqEallyksiIiISGxVTmAImAXcA\nXUCGoCh1qrv378R3MbCKoF/COmAbcLK7ewSxiuySTKYTOHKI0SPDcakQ44AH3f0f3f1Jd/8JcBNw\ndsRxiUjtUl4SERGR2KiYHlPuPm8n41uBC8OHSEXr7a1j+0ypwcaF41IhNhFs3JDvKeBLQ32DNmUQ\nKa9a25SBMeQlUG4SKacazEsiUsMqpjAlUkvq67cBTuHiVF84LhXiAWDKoGOHAM8N9Q3alEGkvGpw\nU4ZR5yVQbhIppxrMSyJSwyppKZ9IzWhqmgqsHWJ0bTguFWIZcIyZXWpm7zGz04GvADdHHJeI1C7l\nJREREYkNFaZEYiiVStLQcAXQTrDxJOHHdhoaFpJKJaMLTkbF3R8GTgPmAv8XuBr4prv//1HGJSK1\nS3lJRERE4kRL+URiKJFI0N6+gmQyxZo1i+nqqmPy5G3MmjWVVGqFtsStMO7+a+DXUcchItJPeUlE\nRETiQoUpkZhKJBK0ti6lowMaG2HlSlBrDxEREREpBTOrB/4FuNLdn4k4HBGpIVrKJyIiIiI7dd55\ncMopwWPQZmEiUgXcvRf4n0Bv1LGISG3RjCkRERER2akLLoA5c6KOQkRK7OfAKcBNUQciIrVDhSkR\nERERERGBYEOEJWZ2NLAO2Jo/6O7XRRKViFQ1FaZEREREREQE4MvAFuAoYEaBcRWmRKToVJgSiaF0\nenv/jp4emDIFFiyA8eODYy0twUNEREREpFjc/b1RxyAitUeFKZEYUuFJREREREREaoEKUyIiIiIi\nIgKAmR0CnAr8NVCXP+bul0YSlIhUNRWmREREREREBDM7GVgJPAkcBjwCHEzwvrEjwtBESiqXy5FM\npshkOuntraO+fhtNTVNJpZIkEomow6t6KkyJiMTMeb8+j32f2heAlsNaaJmmdZ0iIiJSFouBq9z9\nSjP7C3AGsBH4KXBvpJGJlEh3dzczZ55BNnsVkAIM6KOzM0Nb22za21eoOFViKkyJiMTMBU0XMOeE\nOVGHISIiIrXnA8Ct4efbgN3cvcfMvg3cDdwcWWQiJTJ//tKwKJW/EeU4YAbZ7BKSyRStrUsjiq42\njIs6ABEREREREYmFV/M+fwl4X/j5bsD+5Q9HpPQymU7gyCFGjwzHpZQ0Y0pEREREREQAHgI+DmQJ\nZkhdbWYfBGYDv4syMJFS6e2tI1i+V8i4cFxKSTOmREREREREBOAitjc5/wZBoeos4AXgS6W8sJkd\nY2a/NLONZtZnZqeW8noi/errtwE+xGhfOC6lpMKUiIiIiIiI4O5/cPfHw89fcfe57v5+d/+Mu2dL\nfPl3EewCeH5/OCW+nggATU1TgbVDjK4Nx6WUVJgSEZGKksvlmHf+PJo/3wy3Q/Pnm5l3/jxyuVzU\noYlIjcrlcsybdznNzZ8FTqG5+bPMm3e58pJULDObaWZfDh8zy3FNd1/l7t9y95+X43oi/VKpJA0N\nVwDtQF94tA9op6FhIalUMrrgaoR6TImISMXo7u5m5kkzyR6RhZMAg66+Lro2dtF2Yhvtq9q1na+I\nlFWhbca7uvro6tI241J5zOxA4C7gCKA7PLyvmT0KnOruz0UWnEiJJBIJ2ttXkEymyGQW09tbR339\nNpqappJKKYeXgwpTIiJSMeZfOT8oSh2Ud3AccBBkyZJclKT1xtaowhORGqRtxqXK/Ah4DWhw9y4A\nM5sMLA/HjosuNJHSSSQSytUR0lI+ERGpGJlHM3DgEIMTw3ERkTLSNuNSZY4GzusvSgGEn58fjomI\nFJ1mTImISMXopXe43XyDcRGRMtI241JlnqPwe8R6YEOZY9mpSy65hAkTJgw41tLSQktLS0QRiVSv\ndDpNOp0ecGzLli1FObcKUyIiUjHqqQ/26Cn0HrAvHBcRKaPt24wXTkzaZlwqzOXA9Wb2VXf/LwAz\n+zBwHfC1SCMrYNmyZUyfPj3qMERqQqGib0dHB42Njbt87op5BW9m3wJOBaYCW4EHgMvc/cm859wP\nHDPoW//V3b9YrjhFiiH9eJr0E0E1uqe3h/Vb1jNpwiTG148HoOWwFlqm6U6Q1J6mw5vo3NA5sMdU\nv43BuIhIOTU1TaWzcy0De0z10zbjEn9m9udBh94FPGJmb4ZfvwN4i6DHVMl2zDOzPYBD8g4dbGaH\nA39S03WR6lYxhSmgEbgaeAh4J/Ad4F4zO8TdXw2f48AtwLfyvu+NskYpUgQt07YXnjqe76DxlkbS\np6eZvr/uCEltSy1K0XZiG1myMJGgU2IfsBEaHmkgtSoVcYQiUmtSqSRtbbPJZpcQ9JrqT0xrw23G\nV0QboMjOXTLC53lJo4CPAvfmXet74efLgbNKfG0RiVDFFKbc/dT8r83s74GXCW5Prc4besPduxER\nkaqTSCRoX9VOclGSNavW0LW5i8l7TWbWR2aRWpXSdr4iUnb524yvWbOYrq46Jk/exqxZ2mZcKoO7\nLwcws3rgTGCVu78QQRz3o825RGpSxRSmCtgn/PjyoONnmtnfAa8AdwNXuHtxOnKJiEjkEokErTe2\nvj2bcOXZKzWbUEQi1b/NeEcHNDbCypWgtjdSady918xuZuByOhGRkqvIwpSZGbAMaHP3jryhHwN/\nBF4g6EW1FDgc+FjZgxQREREREaksa4HDiOEOfCJSvSqyMAXcAHwQ+Hj+wf5pqKGnzexp4Akz+5i7\nP1DoRNpiVKS8SrnNqIiIiIjskhuB68zsGmAdwaZTb3P3xyKJSkSqWsUVpszseuBzwDHuvmm457p7\np5m9QeH9mwBtMSpSbqXcZlREREREdkl/t/6bC4w5UFfGWKQK5XI5kskUmUwnvb111Ndvo6lpKqlU\nUj35alhFFabM7AbgVOAT7r5+BM8/hGAHv5qZipp+PE36iWA2Sk9vD+u3rGfShEmMrx8PQMth23d7\nk3jL5XJBg+eH18BmaL67OWjwvEgNnkVERESkJA6OOgCpXt3d3cyceQbZ7FVACjCgj87ODG1ts2lv\n14YRtapiClNmdhPQQlCYes3M9guHNrt7j5kdDHyBoOH5y8AHgGuBDqDgMr5q1DJte+GpvzFw+vS0\nGgNXmO7ubmaeNJPsEVk4CTDo6uuia2MXbSe20b6qXUlbRERERIrK3Z+JOgapXvPnLw2LUjPyjo4D\nZpDNLiGZTNHaujSi6CRKlbQd57nAnsD9wKa8x9+E41sJlvj9b+AZ4KdAO3CCu3uZYxXZJfOvnB8U\npQ4iuJEAwW/rQZA9IktyUTLC6GRXmNkCM+szs2VRxyIiAspLIjKQmR1uZreY2YPh4wdm9qGo45LK\nl8l0AkcOMXpkOC61qGJmTLn7sEU0d98AHF2mcERKKvNoBo4bYnAiZFZnyhqPFIeZfRQ4G3iMoE+D\niEiklJek3NLp4AHQ0wPr18OkSTA+6DpBS0vwkGiY2QnALwl252sjuEU6E/idmZ3s7r+NMj6pbL29\ndWy/6z7YuHBcalHFFKZEakkvvcPl7GBcKoqZvRu4FfgH4JsRhyMiorwkkcgvPHV0QGNjUKjSXkSx\n8U/AVe6+KP+gmV0ZjqkwJWNWX7+N4B5IoTc6feG41KJKWsonUjPqqR/6vnVfOC6V5kbgV+5+L0OX\nHUVEykl5SUQGOxT4UYHjPwI+WOZYpMo0NU0lmIxXyNpwXGqRClMiMdR0eNPQe0luDMelYpjZGcDh\nwNfDQ1ouIyKRUl4SkSHkgA8XOD4N6C5zLFJlUqkkDQ1XELSC7guP9gHtNDQsJJVSH91apWkXIjGU\nWpSi7cQ2smRhIkEJuQ/YCA2PNJBalYo4QhkpMzsI+D5wrLtv7T/MMLMTrvn2Nay4ccWAYy0tLbSo\n6YZISaTTadL9TW9CW7ZsiSia0htLXgK45ppLWLFiwoBjyk0ipRFhXvoX4Mdm9h3gwfDYx4BvEOx4\nLjJmiUSC9vYVJJMpMpnF9PbWUV+/jaamqaRSK7TreA1TYUokhhKJBO2r2kkuSrJm1Rq6Nncxea/J\nzPrILFKrUkralaURSAAdZm+/56sDjjaz84F3DN459LIrL2POCXPKG6VIDStUXOno6KCxsTGiiEpu\n1HkJ4LLLljFnjhoBiZRDhHnpOwQzKK8A9g6P5YDvAUtKfXGpfolEgtbWpVGHITGjwpRITCUSCVpv\nbKXj+Q4ab2lk5dkrmb6/3hBUoNXAYXlfG9AKPAl8t9CbPxGRElNeEpEdmFk9MIdg1tRiYN9wqFt5\nQURKSYWpKpTL5YKZNg+vgc3QfHdzMNNmkWbaiJSbu78KdOYfM7PXgZfdvbPwd4mIlI7ykogU4u69\nZvbPwCFhIerFqGMSkdqgwlSV+ed/7uayf5zJ65/JwkmAQVdfF10bu7jjw21879vtnHOOilOlkH48\nTfqJoBdAT28P67esZ9KESYyvHw9Ay2EttExTHw4BginyuvMoInGivCQiEGyZdhhDb8MjIlJ0KkxV\nmbWPzw+KUgflHRwHHASvfybLQ48lOYfWqMKrai3Tthee+pffpU9Pa/md7MDdPxl1DCIi+ZSXRCR0\nI3CdmV0DrAO25g+6+2ORRCUiVU2FqSqTeTQDxw0xOBEyqzNljUdERKKjmZwitSudDh4APT2wfj1M\nmgTjg19/WlqCh8gg/dsC31xgzAk2ShARKSoVpqpML71Db/Y8LhyX2Bv8ZnLK3lNYsHqB3kyKyKho\nJqdI7covPHV0QGNjUKiarl9/Gd5khn43ISJSEipMVZl66oN7GYX+O+kLxyX28t9MSu1JXpZk9S9W\na8MCEYmVZPJCVq8+ilQqqdwkUoXMbDfgPuAkd38q6nhEpHaMizoAKa6mw5uGblW4MRwXkVjbNHMT\ny99czlEnHkUul4s6HBERADZtupbly0/nqKNmKzeJVCF3fwsYD1piISLlpcJUlbn8/Mup//l4eBbo\nCw/2Ac9C/c/Hk/xqMsLoRGREDDgIskdkSS7S76yIxMU4YAbZ7BKSyVTUwYhIaVwPJM1My/lEpGy0\nrqvKLF3aSu+f7oR/vQN2z0BdL2yrh61N9L7+BVKpH9HaujTqMKtWLpcjuSjJmofXwGZovruZWR+Z\npSVZMjbasEBEYulIMpnFUQchIqXRBHwa+IyZ/RfwVt6Yu/tp0YQlItVMhakqk8l0Ail4/SR4ffBo\nH5nMjRFEVRu6u7uZedJMskdk4STAoKuvi66NXbSd2Eb7qvZRFadyuRypZJLOTIa63l621dcztamJ\nZEpFrpqhDQtEJJbG0durjblEqtQW4M4hxrycgYhI7VBhqsoELxSH3pZPLyRLZ/6V84Oi1EF5B8cR\nLMkiWJLVemPriM7V3d3NGTNnclU2S4rgX7QPyHR2MrutjRXtoytySYXShgUiEkt91NdvizoIESkB\nd58bdQwiUnvUY6rKBC8Uh7qZoReSpZR5NAMHDjE4MRwfoaXz53NVNssMtpcZg84esCSbJZVU36Ga\noA0LRCSW1tLUNDXqIESkRMxsdzM72czOM7M9w2MTzex/RB2biFQn3YqvMk1NU+nsXEtQwhhMLyRL\nqZfe4SarjWpJVmcmw1BtZY8EFmfUd6iqOfAcNDzSQGqVGgxXgvTjadJPpAHo6e1h/Zb1TJowifH1\n4wFoOayFlmktUYYoUgR9QDsNDQtJpVZEHYyIlICZTQF+C/wVsAewCngFuBDYG/iH6KITkWqlwlSV\nSaWStLXNJptdQlDCGEfwQnKtXkiWWD31QUGhUHFqlEuy6np7h6txUdervkPV7IAHD+D4WceTWqV+\nYpWiZdr2wlPH8x003tJI+vQ00/efHnFkIsVzwAEXc/zxR5FKrVBuEqle1wH/CZwLvJx3/C7g9kgi\nEpGqp8JUlUkkErS3ryCZTHHPfd9g46sbmPjuAznuk9P1QrLEmg5vonND58AeU/1GuSRrW339cDUu\nttXrV7cOtBEtAAAgAElEQVSapa5JMeeEOVGHISIyQCp1HXPmqNgqUuWOBj7s7m+ZDXgl+ixwQDQh\niUi107vbKpRIJGhtXcpt93ZwZlsj3z06zZxP6YVkqaUWpWg7sY0sWZjI9slqG0e/JGtqUxNrOzuH\nWJAZjIuIiMjYpNPBA6CnB9avh0mTYHyw+paWluAhUoPeBArtlnQAsLnMsYhIjVBhSqRIEokE7ava\nSS5KsmbVGro2dzF5r8nM+sisUS/JSqZSzG5rY0k2O2hBJixsaGBFSn2HRERExiq/8NTRAY2NQaFq\nuu7jidwDXAB8tf+AmY0HrgTujiooEaluKkyJFFEikaD1xta3e8ysPHvlmHrMJBIJVrS3k0omWZzJ\nUNfby7b6eqY2NbEipb5DIiIiIlISlwL3mdljwHigFTgU+DMwN8K4RKSKjagwZWanErR1Ho3V7v76\n6EOSXZG/M1T3yz3w0hSuf3IBK17UzlCllr8soPuVg+H5uzjvvoPZd8/g2GiXBSQSCZa2thY/0Bqi\n3CUicaO8JCJx5u4bzexw4AygkaDl6U+B29z9jUiDE5GqNdIZUz8b5XkdOAT44yi/b0hm9i3gVGAq\nsBV4ALjM3Z/Me847gKsJEuk7CXaUOM/dNxYrjth7ogXSQfVjzx6Ysh72fIrgfgdACzAtquCqW37h\n6bZ7/8jatlO54Oh16u8Vrchzl4jIIMpLIhJrYSH8R+FDyiiXy5FMpshkOuntraO+fhtNTVNJpZJa\nMSFVbTRL+fZ39xdH8kQz+8sY4xlOI0HR6SGCotN3gHvN7BB3fzV8zrXAccDJBM35rgZ+ZWaN7t5X\ngphiR806RXYQde4SERlMeUlERAbo7u5m5swzyGavAlIEk9X66OzM0NY2m/Z27bAu1WvcCJ/3E2A0\nU8hvA4r6QsrdT3X3tLt3uXsn8PfAX0OwcZmZTQDOAi5x94fc/b8J1kF/EDi2mLGISMWIPHeJiAyi\nvCQiIjuYP39pWJSaQVCUguDt+gyy2SUkk9r8SKrXiGZMufvc0ZzU3c8dUzSjs0/48eXwYyOwG3Bv\nXhwvhY37ZgK/LUNMUsPU3yt+Ypq7RKSGKS+JiEghmUwnwUypQo4kk1lcznBEyqoid+UzMwOWAW3u\n3hEe3g94zd1fG/T0FwhmVomUVMu0Fo7d71iSyRRPrOmErvfTPXkbh856v9aFS03LL9r29Pawfst6\nJk2YxPh6FW1FRESiZmYXAv/i7m+Y2XuADbXSBiVOenvr2D5TarBx4bhIdRrprnw/I2i+OdRvSv+Y\nu/tpRYptODcQLNH7+K6e6JJLLmHChAkDjrW0tNCiRk0ySoXWhXd19dHVpXXh+dLpNOn+7QtDW7Zs\nKcm1Ypi7alLLtO2Fp47nO2i8pZH06Wmm76+NAaT2KC+JxFP+7so9PbB+PUyaBOPDDYSqvI/rtcAK\n4A3gGYIb/t1RBlSL6uu3MfR/D33huEh1GumMqS0M/yKq32i3Px41M7se+BxwjLtvyht6AdjDzPYY\nNGtqf+B3Q51v2bJlTJ+uN0ey6wauC+83cF14a+vSiKKLj0KF346ODhobG0txudjkLimOwbOvpuw9\nhQWrF2j2lVQS5SUZUo0XRyKV/3fb0QGNjcG/RY28TcgBp5vZ3eHXB5nZ+EJPdPdnyxdWbWlqmkpn\n51oGvpfot5ampqnlDklioFZ2aixJj6lSMbMbgFOBT7j7+kHD64C3gE8Bvwyfvw9wGLCgnHFKbdK6\n8PiJS+6S4smffSVSiZSXZDg1XhyR6Pwv4DqCVSkw9E19B7SerERSqSRtbbPJZpcARxLc4O4D1tLQ\nsJBUakW0AUrZ1dJOjWPuMWVmBxAspwP4/aDZS0VnZjcBLQSFqdfMbL9waLO797j7FjP7IXCNmeWA\nzcDVwO+B1aWMTQS0LrxSlDt3iYjsjPKSiETJ3a81s58CE4FHCXY0f3n475JiSyQStLevCGfHLB40\nO6Z6ChAycrW0ImfUhSkz2wNYDpzG9nfhbmb/Dsx199FsgTwa5xJU6e8fdHwuwdbLABcTFKN+BbyT\noCB1srtrOryUnNaFx1uEuUtEpCDlJRGJC3f/E/AnMzsLeNDde6KOqRYlEomqKTTIrqulFTnjxvA9\n3wOmAccD7w4fJwAfDsdKwt3HuXtd+DH/8ZO852x19wvdfR9338PdT3X3jaWKSSRfsO577RCjWhce\nA5HkLpGo5XI55p0/j+bPN8Pt0Pz5ZuadP49cLhd1aKK8JDUql8sxb97lNDd/FjiF5ubPMm/e5cpL\nMeDuy929x8xmmtmXw8dRUcclUotqaUXOWJbynQ6c4u4P5h1bbWbzgF8QzGwSqTm1sC68wpuyKndJ\nzenu7mbmSTPJHpGFkwCDrr4uujZ20XZiG+2r2rU0IFrKS1JztItxvJnZvgSrTz5C0BQdIGFmvwM+\n5+6qHoqUSS2tyBnLjKl3UXj70O5wTKQm9a8Lnzv3TiZPPhk4hcmTT2bu3Dur5kVWSwv84hfB45/+\nCZ5+OvjYfyzGRSlQ7pIaNP/K+UFR6iC2v6YZBxwE2SOyJBclI4xOUF6SGjSwZ0p+YtreM0UidT3Q\nCxzi7n/t7n8NTAG2hWMiUia1tCJnLDOmHgIWmdk8d38LwMx2BxYB7UWMTSI2eFv29VvWM2nCJG3L\nPoz+deH9O+msXKmddGIkstxlZt8i2LhhKrAVeAC4zN2fLOV1RTKPZuC4IQYnQmZ1pqzxyA6Ul6Tm\n1FLPlAp1InCMu2f7D7j7H8zsPGBNdGGJ1J5aWJHTbyyFqYuA/wQ2mtk6glsdjQR/Q58uYmwSsfxt\n2Tue76DxlkbSp6eZvr8qLVKRosxdjQQbMzxEsDHDd4B7zewQd3+1xNeWIdRC8b2X3uFaEwTjEiXl\nJak5tdQzpUKNA94qcHwrY1ttIyJjVEs7NY66MOXuj5vZB4Avsn1r418Ct7v7n4sZnIhIsUSZu9z9\n1PyvzezvCbZhnkGwe6hEoBaK7/XUD9eaIBiPQC0UBUdCeak6DO6/OGUKLFhQMf0Xy66WeqZUqHuB\n75vZF/v7SYV9p64lKKSLSBnVyk6NY3pF6u4vAzcUORYRqQC5XI5kMsWaNZ1AHc3N25g1ayqpVDL2\nVfsY5a59wo8vRxqFVL2mw5vo3NAZ9JgabGMwHoVaKAqOlPJS5VPhaXSamqbS2bmWoAY6WHX1TKlQ\nFwC/BTaZWf9yvoOBPxDsGioiUnRjKkyZ2WTg48BeDLrd4e7XFSEu2QW5XI5UMklnJkNdby/b6uuZ\n2tREMpWKfeFA4q3Sd9KJQ+4yMwOWAW3u3lGOa0rtSi1K0XZiG1myMJHtrQk2QsMjDaRWqclw1JSX\npNbUUs+USuTuz5rZNIIiVP9MzieA/3B3rf+uUf03pjOZzkHLyeJ/Y1oqw6gLU2Z2LsGODK8BhaaZ\nqzAVoe7ubs6YOZOrstmwbBD8V5/p7GR2Wxsr2rU1eKnUwlT+gTvp9Bu4k05cp5rGKHfdQPBC7+ND\nPeGab1/DihsHvjBvaWmhpdJ/gKTsEokE7avaSS5KsmbVGro2dzF5r8nM+sgsUqt0s6JfOp0m3Z/A\nQ1u2bCn5dSspLwFcc80lrFgxYcAx5SYZrfyeKWvWLKarq47Jk/tnX8f7Blc5RZWXAMLNGH4VPqTG\nFboxDX10dlbGjWmpDGOZMfUd4OvANe7uRY5HdtHS+fO5KpstUDaAJdksqWSSpa2tEUVX3aqh8LQz\nFb6TTuS5y8yuBz5HsNvNpqGed9mVlzHnhDnlC0yqWiKRoPXG1reXzK08e2VNLpkbTqHiSkdHB42N\njaW+dMXkJYDLLlvGnDn62ZFdp12Mdy7CvCQyQCXfmJbKMZbC1DhghYpS8dSZyQxTNoDFGW0NLmNX\n4TvpRJq7zOwGgq3ZP+Hu66OIQURiR3lpFAbPTF6/HiZNqq6ZySIicVPhN6alQoylMPVjoJmgF4HE\nTF1v73A7g1PXq6XhMnYVvpNOZLnLzG4CWgjeAL5mZvuFQ5vdvafc8Uhp5HK5YMncw2tgMzTf3Rws\nmVukJXMyJOWlUcgvPPXPtEmnNdNmOJW8YYnUJjM7D7gc2A/4PXCxu/+faKOqbRV+Y1oqxFgKU0ng\nbjM7EXiSoIURBD+t7u6XFis4Gb1t9fXD7QzOtvpotgaX6lDhO+lEmbvOJajo3T/o+FzgJyW8rpRJ\nd3c3M0+aSfaILJwEGHT1ddG1sYu2E9toX6X+flKQ8pKUTKVvWCK1x8xmA9cAXwIeAs4BfmNmU939\nuUiDq2EVfmNaKsRYqhTfBD5NUMHePe+4EfzESoSmNjWxtrNziLJBMB6F9ONp0k8E8+97entYv2U9\nkyZMYnx9MP++5bDtW4dLfFX4TjqR5S53H1fK80v05l85PyhKHZR3cBxwEGTJklyUpPVG9feTHSgv\nScmoL4yMhZl9BHjT3R8Pv/4CMA94GrjC3V8v4eUvBW5y9zvCrxea2WeArwBXlPC6MowKvzEtFWIs\nhakLgb9199uLHYzsumQqxey2NpZks4PKBrCwoYEVqWi2Bm+Ztr3w1N+AN316Wg14K0yF76Sj3CUl\nk3k0A8cNMTgRMqvV308KUl6SklFfGBmjHxIUzR83s/cBtwErgc8C4wlmWxadme0OTAeuHDT0n8DM\nUlxTRqbCb0xLhRhLYepN4IFiByLFkUgkWNHeTiqZZHEmQ11vL9vq65na1MSK1Oj7nKhnigxWwTvp\nKHdJyfTSO1z7hWBcZEfKS1Iy6gsjY3QI8Gj4+d8A97j7F83sY8DPKFFhCtgHqANeGHT8RYJ+UwU9\n+eSTJQpH8v3gBwv5/vdv5oknLmfbtnHU1fVx2GEHc9FFC3nuued47jmttKxVxfodHEth6jrgAuBr\nRYlAii6RSLC0ddeXjKhnilQZ5a5R0PLb0amnfrj2C8G4yI6Ul6Rk1BdGxsgIZkYBzALuDj9fD/xV\nBPEMu6z5zDPPLFccMkhX1wP88pc/jToMqRJjeaX8UeBTZnYyQaNOZ/v/eu7upxUxPomQeqZIlVHu\nGgUtvx2dpsOb6NzQOTBf9tsYjIsUoLwkJaO+MDJGHQS9nVYDnwQuDo+/hx1nMxXTS8A2dpwdtT/w\n/FDfdOutt3LooYeWMCwRGc6TTz5ZlALxWApTWwimcRai5udVpBZ6pqTTwQOgpwfWr4dJk2B8eJ8o\nf2tqqXjKXVIyqUUp2k5sI0sWJrK9/cJGaHikgdSqaPr7SewpL0nJqC+MjNFFwL8CzcDV7t6/Tud0\nSrj02N23mtk6gg0h7s4b+iTwm6G+79BDD2V6hfSUEJGhjbgwZWbvdvdX3X1uCeORGKmFnin5haf+\nnknpdMX0TCq7wYW8KVNgwYJ4F/IqMXddn7meFS8Hbxi0ZG6guBaTE4kE7avag558q9bQtbmLyXtN\nDnryrVJPPhmoEvOSVJ4K37BEIuLuDwPvKzC0kGBGUyl9D1huZg8BvwP+IYzln0t8XRGJ2GhmTL1k\nZvcBvwB+4e4bSxSTxEQxe6bkv5nsfuVgeP4uzrvvYPbdMzgWx4KGFHBYGlrCf8jeHtiyHiZMgrDv\nEIe1ALH7h6y43HXTZ2/S3b8hxLmYnEgkaL2x9e2ljyvPXqmljzKUistLUpkqeMMSiZCZ7QucARwI\nfNfd/wR8kKAR+YZSXdfd7zCzvQm2k9wfeBz4jLurs7ZIlRtNYer9wKkE0zqvNbPHCF5Q3eXuj5Ui\nuHI479fnse9T+wKamTBYMXum5L+ZvO3eP7K27VQuOHodcz6lV0eVpEL7DlVl7hIpt2LOVtPNCuUl\nEYknM2sC/oOgr9MhBLOV/gR8FjiUEt+BdPebgZtLeQ0RiZ8RF6bcfT3B7jHXmdlewGcIXlRdZmab\ngbvCxxp3r5htPi5ouoA5J8yJOoxYUs8UqQbVmrtERqKYBaBizlar9ZsVyksiEmPfA25y94Vm9pe8\n478Gzo0oJhGpcmPav9rdNwO3A7eb2e7AJ4BTgFZgTzP7qrvfVrQoJRLF7pmSy+VILkpyzwNr4A2Y\n/7NmVn9sFqlF0fZfyeVyYf+FTqCO5ub+/gtJ9V+oMspd0Yjr7JhKiGtXZybVQgEorn3HRkp5SURi\nphEodNf+RUAvjEWkJMZUmMrn7luB34aPr5rZdKBuV88r8VCsnind3d3MPGkm2SOy8HnAYGNfF8s3\ndtF2Yhvtq9ojKQJ1d3czc+YZZLNXESxnN7q6+ujqytDWNpv2djUHrVZxzl3nnQf7BiuMx7w8Kk5v\n0ONaHClmXHGdmVQLqunvK855SURqxivAngWONxAUp0REim5EhSkz+9BIT+juHWMPZ6dxHANcDkwn\naIj3P939rrzx5cDfDfq2h9x9ZqlikpGZf+X8oCiV369qHHAQZMmSXJSk9cbW8sc1f2lYlJoxKLAZ\nZLNLSCZTtLYuLXtcUhxxyV2jdcEFMGcMK4yL+QY9rrOJ4iquxTeJn0rNSyJSM+4Cvmlmb78SMbP9\ngKXAv0cWlYhUtZHOmHp0hM9zSntn713AI8APgTvD6w2+/m+AeXnHtpYwHhmhBx9+EE4aYnAiPLjq\nwbLG0y+T6SSYKVXIkWQyi8sZTkXoX5K55uE1sBma724OlndGvCRzCHHJXRVHhRaRkqnYvHT99bBi\nRfC5itMiVetygn5SzwPvBO4huLX8ELAwwrhiq78tSCbTSW9vHfX122hqUlsQkdEYaWHq4JJGMULu\nvgpYBWBmhZ5iwFZ37y5nXLJzL7yUC/51ChkXjkegt7eO4QILxqXfgCWZJwEGXX1ddEW8JHMYschd\nIiJ5KjYv3XRTZS6RFJGRc/ctZnY08EmCflPjgA53vyfayOKpUFsQ6KOzU21BREZjRIUpd3+mxHEU\niwOfMLNugplS9wEL3H1jtGFJz2tvBf86hWpAfeF4BF6b/Bw0njLEqPPayxvKGk/cxXVJ5lAqKHdV\nvbhufiBSbspL8aHNT0QKc3cH7g0fMgy1BREpjjE1PzezccARwH4Mmmbu7r8oQlxj9SsgDTwDvBdY\nDKwxs2nu/kaEcdW88bYXWze8OrCg0W9DMB6F4/Y/luXLT2fgfyb92jlu7p3lDinWMo9m4LghBidC\nZnWmrPGMVoxzV1WL6+YHInGgvBQNbX4isp2ZXcSOLVIKcvfrShxORVFbEJHiGHVhysw+QFAAGmoq\n+rhdimgXuHt+Q76nzWwd8BxwGlBwq+XkZUlW/2K17tqX2H57vp9X/u0d0JyFAwl+SvqADcDKBvbb\n772RxJVKJWlrm002uwQ4Mi+wtTQ0LCSVWhFJXHHVS++wSzJ76S1rPKMR59xV7Sptpp1IuSgvRUez\nHEQGuIQRFqYAFabyqC2ISHGMZcbU9cBjwEeBZwnWHk8Avg8sKF5ou87d/2RmXRSepwPApr9sYvmv\nlnPHbXdw9Iyj2X333WlpaaFFHT2LaubMI3h6+WXwr3fA7hmo64Vt9bC1CV7/AjNPuy+SuBKJBO3t\nK0gmU9xz3zfY+OoGJr77QI775HRSKd0tHaye+mGXZNaPIKWk02nS/du9hbZs2VKcAIdXMbmr2lT6\nTDuRElJeiohmOYhs5+7vjTqGSlVfv43hXhwH4yKyM2MpTM0EjnL3P5uZA33u/jszuxy4gWA6eiyY\n2QRgEsG8nMJOBA6A1597nf3fsb/u2pfIgJlJr/+QOM1MSiQStLYu5bZ7OzizrZHvHp3WzmNDaDq8\nic4NnYVLvRuD8Z0pVPjt6OigsbGxSFEOqWJyV7Wp5Jl2IiWmvBQRzXIQ2Tkz2w3A3aNpBlsBmpqm\n0tm5lsJtQdbS1DS13CGJVKSxTBF34M/h568A+4efvwCU9DfPzPYws8PN7PDw0MHh1weFY4vNrNHM\nJprZUcAvgJeBn+305BPDu/pSEv0zk+bOvZOJk46Dvd/PxEnHMXfunerjUEFSi1I0PNIQLJDtCw/2\nAc9BwyMNpBYNdfc5FiLLXbXu7Zl2hYxwpp1IlVJeisj2WQ6FaJaD1DYzu9DMngbeBN40s6fN7OKo\n44qjVCpJQ8MVQDsDXxy3hzffk9EFJ1JBxvJu4AngQwRvTdcCl5vZVuB8gmnopfRRtu8O4cD3ws+X\nA+cRNAk6B/grghd6q4G/c/fXdnpm3bXfQfrxNOkngiVXPb09TNl7CgtWL2B8/XgAWg5roWXayJc8\namZS5UskErSvaie5KMmaVWvo2tzF5L0mM+sjs0itin2ftihzV00rxkw7qT7aqRFQXoqMZjlIIdqp\nEczsO8BFwDLgofDwDOBKM0u4+8LIgouh/LYgmcxienvrqK/fRlPTVLUFERmFsRSm/hHYLfz868Aq\nghLxFmBOkeIqyN3vZ/hZXkN1Mdk53bXfQcu00RWepDYkEglab2yl4/kOGm9pZOXZK5m+f0UUGCPL\nXbUutShF24ltZMnCRLav5N0YzrRbFeuZdhUt/wZD98s98NIUrn9yASteHNsNhmLRTo1vU16KiDY/\nkcG0U+PbvkJwY//necd+Y2aPAD8EVJgapP/mu4iM3agrMe5+d97nT5tZA8HU85fcfWsxgysr3bUX\nqWpVm7sqQP5Mu3vuWsPGN7qY+M7JHPexiphpV9HybzB0dEDjV+GmdTA94lqydmoMKC9FJ3+Ww5o1\ni+nqqmPy5P7ZMTVTgJA82qnxbXXAIwWOPxqOiYgU3agLU2a2F1Dn7n8CcHcHNpnZ3mb2lru/Uuwg\nS8rZ3h9Hd+1rTjoNy5fn6HwmyZ9ebQc/gC/f8kUWvPsopr43xdy5CbRBY3WoutxVYfpn2m1fyrtS\nS3lrmHZqDCgvRat/lkNHBzQ2wsqV0RdtJTraqfFttwHnEszizPdl4PbyhyMitWAsa9dWAmmCqZz5\nTgO+ABy/q0GV0wEPHsDxs47XXfsSS6eDB0D3KwfD83dx/X0Hs+La4FhLC5EUgD796W6+efVMNhyd\nhQMBgzf6YMPGp3jHI20ce2w7oJ+LKlFVuUukkmmnxrcpL4nERC3v1Ghmy9i+G4AD55vZiQzsMdUA\n/DiC8ESkBoylMNXfYHyw+4Brdi2c8ktdk2LOCWrjUGr5haeO5/9I4y2nctPZ6yLvTaTlJDWlqnKX\nSCV7e6fGQu8Ba6vno/KSSExs36mxcGKq8p0aj2DgNpUd4ccPhB+3hMcOK2dQIlI7xvLKbxyFG5CP\nY3sDT5GKoOUkNUW5S3agneGioZ0a36a8JDvQznDRqOWdGt39E1HHICK1bSyFqYcJ1h1fNuj4OcC6\nXY5IpIy0nGR08nf46untYcreU1iwegHj66Pd4WuElLtkAO0MFx3t1Pg25SUZQDvDRUc7NYqIRGcs\nhakrgP80s2nAvQRv6z8FHI16IVSV/L5QPT2wfj1MmgTjgxrEqPpCxbWgoeUko5O/w1cFUu6SAbSU\nNzraqfFtyksygHaGi04t79RoZj8DvuTur4SfD/Xq2N39tPJGJyK1YNTvut39ATObASSBvw0PPwoc\n5e6FthaVCjWgL1S4Y006PbYda+Ja0NByktoRde4ys/OAy4H9gN8DF7v7/yn1dWVoWsobLe3UqLwk\nO4rrznDFvFkZZzW8U+MWtveY6v+8YGGqbBGJSE0ZdWHKzMzdHwW+WGDsXe7+elEiEykDLSepHVHm\nLjObTdDI+EsEO9ycA/zGzKa6+3Oluq4MT0t5JWrKSzJYXHeGK+bNSokfd59b6HMRkXIp1HBzZ24o\ndNDM9gB+vWvhiJRX/3KSue+Yy+RVk+F2mLxqMnPfMVf9ZapPlLnrUuAmd7/D3Z9194XAH4CvFHpy\nMnkh8+ZdTi6XG/WFcrkc8+ZdTnPzZ4FTaG7+7C6fa/5Zl8P1U5h/1uWxOteu/hnfXspbyBiW8sbx\nz1gJ54rb31eZVUxekvLYvjNcIdWxM1w6DaecEjwWLIApU4KP/cf6Z2ZJNMzsXjPbq8DxPc3s3ihi\nEpEa4O6jehC8aFk86Ni7gTbg/4z2fFE9gOmA37rqVpedW7fOHYKP1WrdpnXOInzdpir+Q8bUunXr\nnOCV+HQv3e98JLkL2B14C/jMoONXA/cPOjY9+Hv4nUO7NzR80ru7u0f89/jiiy96Q8MnHdod+hzc\nYZvONYTZ82Y7f4+zqMDjLPyMs86o+D+jzjW6c+VTXtoxN62L0YuAYr4uidNrnLlzvxb+LHuBx4M+\nd+7XxnTeav37KpW4/hnLlJf6gH0LHE8A20p13THEGbu8JFKLipWXxjJj6jjgLDO7FMDM/gfw2zCY\nE8Zwvkh9/8tJLp83rxLuqorIrokqd+0D1AEvDDr+IkFflwIGNrodqYFNc/uXguhcQ7E39oZ/mwjP\nErwMJ/z4LLByIrz+/0USl84V3bkiUEF5ScohlUrS0HAF0M7AxNQe7gyXjC44qWpm9iEz+3D45QfD\nrz+Ud3wuQY4QESm6sTQ/7zKzE4D7zGwb0AL0AJ9199eKHWCp3fTcJrYuX84xd9/BxXd8j3NmnRN1\nSCJSAjHMXSNoIDq6RrfFbJpbC+d67LFn4JUO+Nf5sHsG6nphWz1sbYLX/4nHHjtrxOe65/nV0PLU\nEKPOPc9vGPG54vr3VQvnKrdKy0tPPvlkueLYqf5QihFSMc9VDD/4wUK+//2bWbfucjZtGscBB/TR\n2HgwF120kOeee47nnht9C7Bq/vsqhbj+GUv8O/ho3uf/WWD8TYKNGkREim7UhSkAd3/czE4G7gHW\nAp9z9zeKGlmZjANmAj/qfp07lz8EKkwNkMvlwm1zO4E6mpv/H3v3Hx9XXeb9/3UlAQqKRXFUrFhK\nJG4DXaHBtHR1qyguiFR36X2XUdZN/f1z17LLpF+6ssG77cp0tasI+sVd01VkNtrFBVYtUsGahbGD\nDd7CBt11iBUqkFCgiFAgzXX/cSY0GWbSzGQy58zM+/l4nEeS85k5c2UyuTK5zudcn/FlcxPqvyQ1\nJ6Tc9TBwgOfPQjgOeKDwXdYAcwHYvXsXK1asIB6PEz/EkkeVbJrbOMd6GTzZCwVaTJdyrBcMHQ83\n3a2gBugAACAASURBVFB8vG1FiXFF9fmqz2OlUilSeY1t9u3bN+0YZqJ28hJceOGFsxlTWSoZUgS/\nPQB++1v47W9v48YbvzHjYzXC81VJjfA9TnBi7uO9QCdBnhh3ABh296erHpWINIRpFabMrNiSxU8T\nrGV2m5kZ4O5ek+tzLAEuvllLg080PDzMsmUX5C6RSALG0NAYQ0MZ+vtXkU73qTglkRaF3OXuz5jZ\nLuAtwPcmDL0Z+H7he20maJ0wxvz553HDDcULHhMdbJpb6J/00prm6lg6ViMdq1Dhd2BggI6OjmnH\nMV21m5fgmmuuYeHChbMRUsnuuScoGlxzDcw0pEoeq5Ki+j1G9fmqpKh+j/fcc8+sFYjd/de5T8tp\n9SIiMiPTnTF1/TRvN41LU6KpCXjJC7Q0+EST+3aMm9y3o7d3U0jRiUxLVHLX54EtZvYT4A7gA8Br\ngK9MfbeddHa2T/tBOjvbGRzcyeTfWR1Lx9KxIqZm89LChQtZvDha5x8XLoRKhVTJY1VSVL/HqD5f\nldQI3yOAmU17Wq+7T+9smYhIKWbSOb2WN8ZXcsgtdXIA/O3t7VO3nG8w7e1vn7DCUf52wNvb3x52\niBWlVfnCU41VZsLeCJZgHyLoH3MH8IYCt5mwKt/tJa8oNjw8nFud7PbcqmSe+6hj1dKxvnLbV/yo\n9x/rxN/gxN/hxM/LfXyDH/X+Y/0rt32l5r/HqB5rIuWlAu+ZIrT6VSOsMhfV7zGqz1clRfV7nK28\nRNBhf1pbJR93hjFHLi+JNKIwV+WrSzuB9s7OsMOIlEr2AImq1F0pVqRWsCK1grXb19J2bBtrt699\nbl/qrtShDyIyDe7+ZXdf4O5z3P317v6fxW77yld+iq6u60q+XDYWi5FO99HVdR0LFpwHrGDBgvNm\nfKx588+CY1/LvPlnRepYUf0eZxrXh5d9mF///T10HbGUebc/CT/4JfNuf5KuI5by67+/hw8vm34v\nxNl6vur1uW80peQlEalf7t403S3sWEWkTk2negU8Arx0utUugsW258+kYjbbG7kq+x3gt4O/ubW1\n7LOq9arRZkzJ9AwPD/vfdHX529vb/by2Nn97e7v/TVfXjH5/ZvEMYE3lrvG8dM01Mz/7V8mzvdf8\nMJhNeM0PZ36wSh4rqt9jI8TVGN+j8tKEGCI3MyGqr+dKiur3GNXnq5Ki+j02wkzO6W5RzEsijahS\neWm6PaaOAd5uZo9N47YGvBSoiek0f9ZyJPNOOJGv3fBtnVXNU4N9O2SWDQ8Pc8GyZWzMZnPt8IN5\n3ZnBQVb199OXTkft96huc1c1jIyMkOhJcPNtO+Ap6P7OSrb/0XKSPcmo/ZxFaony0gxotWCR2WVm\nf8cUPe7c/TNVDEdEGsR0C1MAW2YriDDdN/pj7vvVKOed93FN+c+TTCbo719FNruBYN3CJoIyxE5a\nW9eRTPaFG6BU3abubjZmswXa4cOGbJZkIsGm3t6QoitqS9gB1KLh4WGWnbOM7GlZeBdgsGdsiC17\nhug/u5/0tsgVIUVqyZawA6hFWi24NKlUsAHs3w9tbbB2LcyZE+yLx4NNJM+fMrkw1QScmNuXBVSY\nEpGKm1Zhyuv6emKtMlfMeN+O4MzkeoaGmlmwYPzMpN78NaLBTIZkkbElwPpMpprhHFJ9567Z1X1Z\nd1CUOn7CzibgeMiSJdGToPfKyBUhRSJPeal8Wi24NCo8STnc/dT8fWb2AuBrwHerH5GINIJSZkzV\nuSVkMuvDDiJyYrEYvb2bGBiAjg7YurUxls0t18jICMlEgsFMhubRUQ60tNDe2UkiWR+XPjWPjk7R\nDj8Yl/qQ+VkGzioyOA8y26NVhBSR+pfJDMIUp0f0Pk5kdrj7783sUuAm4OthxyMi9UeFqefUxypz\nEp4a7L9UsgMtLTiF12ocy41LfRhldKpFOYNxEZEqaoTVgkUi7EXAy8MOQkTqk/6LfM4YLS0Hwg5C\naliN9l8qSXtnJzsHB4u0ww/GpT600MJUVcgW/fkQkSoL3qcVT0x6Hycyc2b2Vzy/+fnLgL8AflD9\niESkEdRUnwMz+2Mzu9HM9pjZmJm9s8BtenLjT5rZrWY2zaXjtMqczMxgJsOSImNLcuO1LpFMcklr\nK2mCGVLkPqaBda2tJJLFLrGQWtN5aifcX2RwT25cRKSKgvdpO4uM6n2cSIWsyds+BZwLfBt4b4hx\niUgdq7VT3kcBdwL/DFxHXjXfzLqBjwPvIVg1Yh1ws5m91t2fKHzI4N9qrTInM9UI/ZdisRh96TTJ\nRIL1eX20+uqkj5YEkj1J+s/uJ0sW5nFwUc490HpnK8ltKkKKSHVptWCR2efuJ4Qdg4g0npILU2b2\nY4LC0Lfc/anKh1Scu28DtuXiyI/LCCr6n3H3H+T2fZjgnP+7gasLHfOVr/wUb3vbGVplTmasUfov\nxWKxmrwkMczcVYtisRjpbWkSPQluvn4He54aYt6RCzjrj5aT3KYipEglKC+VRqsFi4iI1Kdy/lO+\nA7gcuMLM+oCvuXu6smGVZQFBQ74fju9w92fNrB9YRpHCVDL5Rd7zHi0zV0gqFWwA+/dDWxusXQtz\n5gT7tAzxZOq/FHlRzV2RFYvF6L2yl2/eMsCF/R1c/satvOdM5UuRClJeKpFWCxaZXWZ2FPA3wJuA\nY5h8ztXdXb9xIlJxJRem3P2vc5fMnQu8D9hhZr8CeoGvu/tDFY5xul6R+/hg3v6HgNYqx1IXVHgq\nTSKZZFV/Pxuy2bwLDIL+S33qvxSqCOcuEWlQyksiEkHXEJzU/xbwSN5YflN0EZGKKOvaIncfBa4H\nrjezlwMfBP4PsNHMvgdcOX45XQQogUpVqP9S9NVY7hKRBqC8JCIRcw6w3N1rf9UeEakZM2p6Y2ad\nBGf4VhHMTPoXgplL3zGzf3L3v5p5iNM2PlPqFUyu7h8HPFDsTp/73Br6+uZO2hePx4lrqpCUoVb7\nL1VTKpUiNX6NaM6+ffuqGkPEcpeIiPKSSB3Jb4exezfMn18z7TB+DRRZNEpEZHaU0/z85cCfA6uB\n1wA3AnHgJnf33G22ADcD1XwTNURQnHoLMJiL4zDgDcDfFrvT4YdvBoJLpSP+R0KkLhQq/A4MDNDR\n0TGrjxvh3CUiDUp5SaQ+TfyfYrwfWipVM/3QLgY+a2Yfcfffhh2MyFRGRkZIJJJkMoOMjjbT0nKA\nzs52ksmErlapMeXMmLoPuJdgFZl/cffhArf5L4KGnhVlZi8ATpqw60QzOxXY6+73mdk/Ap82s1/k\nYrwEeBa4ttgxr7qqZv5IiMjMhJa7RESKUF4Skai5g6A4db+Z/Y6gZeo4d/eXhBOWyGTDw8MsW3YB\n2exGIEnQp3+MwcEM/f2rSKe1WmstKacw9VZ3//FUN3D3fQQrOVTa64Fbxh8G+Hzu8y3A+9w9aWZH\nEkx/fzHwE+Bt7v77WYhFRGpLmLlLRKQQ5SURiZoUECNYmS+/+blIZHR3b8oVpSauid4ELCWb3UAi\nkaS3d1NI0UmpylmVb8o3ULPJ3X9E8Gqb6jaXAZdVJSARqRlh5q5Gl7orReruoNnG8CP74eE2rrhn\nLX0PBc024qfEiS/SddSNRK+JgPKSiETQUqDT3e8OOxCRqWQygwQzpQpZQiazvprhyAyV02PqTg6u\ndGe5j57bngb+h2A6+i0F7i4iEgrlrvDEFx0sMgwMQMcn4Kpduoy6kek1EVBeEpEI+iVwRNhBiBzK\n6GgzB/905mvKjUutmHL2URHbgBOBR4GbctujQCtwO3AscLOZvbdSQYqIVIByVwlSKVixItiu+MyJ\ncO31XPGZE5/bl7ewooiUR3lJRKKmG/i8mS0zs2PM7EUTt7CDExnX0nKAg+d28o3lxqVWlNNj6sXA\nRnefNG/OzC4G2tz9HWb2/wFrga9XIEYRkUqomdx1xRXQ1xd8XspqofnLU7e1wdq15S1PPWlFoQfu\npePqd3LVh3ax+Lj6mdIy8fkafvxEeOB6rrj1RPr+MdgX1nMvDaVm8pKINIxtuY//WWDMAU1DkUjo\n7GxncHAnk3tMjdtJZ2d7tUOSGSinMBUHTimwvw+4G/hg7nP1eRKRKKmZ3FXuaqFRLX5EtWhTyeJb\nJb8HFcxKU+PfY83kJRFpGGeGHYDIdCSTCfr7V5HNbgCWEFwMNgbspLV1HclkX7gBSknKKUw9DZxB\nsMTxREuA/ROO++QM4hIRqTTlrpBEvDAQOVEtmFVSRYtJp6QgnjvY6H7YtxvmzoeW3MFOiRPUfyJJ\neUlEIiW32FTVmdk64FzgVOBpd39xGHFI7YjFYqTTfSQSSTKZ9YyONtPScoDOznaSyT5isVjYIUoJ\nyilMfRHoNbPXA3fk9nUCHwE+m/v6T4A7Zx6eiEjFKHeJzMBsXSo6U5MaqT8wQMfVHaTOT9XKZafK\nSyIigcMIZojeDrw/5FikRsRiMXp7N4UdhlRAyYUpd19vZg8BHwU+kds9CKxx96/mvv4n4KuF7i8i\nEgblLpGZiersq1qmvCQiEnD3HgAz6wo3EhEJQ0mFKTNrAdYBX5vwhul53P2pmQYmIlIpyl31o8b7\nCYk8R3kpXMolIiIi0VFSYcrdR3MrxfzTLMUjIlJxyl31Q/8sSr1QXgqXcomIiEh0lNNj6ofAGwiu\nARYRqRXKXSISNcpLIhGhWXSVZ2Y9wKWHuNnp7j5Q7mOsWbOGuXPnTtoXj8eJ64clUnGpVIrUeKLM\n2bdvX0WOXU5h6nvAP5rZqcAu4JmJg+5+QyUCEykmdVeKLbdvYfjaQZ791aPY6DN4y+Ec9poX87J3\nt9O1rOu5RrgiEyh3Sc0YGRkh0ZNgx093wGOw8nsrWX76cpI9Sa0yU1+Ul6RmjIyMkEgk2bFjEGhm\n5coDLF/eTjKZqIu8pMJTwMzmAV8AzgSOyRt2d28u4XBXANce4ja7Szje82zevJnFi2tisQuRmleo\n6DswMEBHR8eMj11OYerLuY/dRcabyoxFZFre8vK38NVNn+bL2ftZAhgwxrNkfvt7LtlzBG9NvzXs\nECWalLukJgwPD7PsnGVkT8vCOYDB0NgQQ3uG6D+7n/S2dF38EyiA8pLUiOHhYZYtu4BsdiOQBIyh\noTGGhjL0968indbS7HXkm8CLCfLSyEwO5O57gb2VCEpE6lvJb3jcvWmqbTaCFJloU3c3G7NZlhIU\npSB4IS8FNmSzJBOJ8IKTyAojd5nZAjP7hpn9xsyeMbP7zOxyMzt8Nh5P6kP3Zd1BUep4Jie54yF7\nWpZEj3JcvVBeklrR3b0pV5R6/ruvbHYDiUQyvOCk0pYC73H3r7r7v+dvs/WgZvbq3OzRVwPNZvY6\nMzvVzF4wW48pItFRzoyp55jZUcBT7u4VikfkkAYzGYq9/VkCrM9kqhmO1KAq5q6TgMeBC4EscArw\nNeCFwMdn+bHlEFJ3pUjdHVwnv390P23HtrF2+1rmtAQNReKnxEO5LDjzswycVWRwHmS2K8fVI+Ul\nibJMZhCmePeVyayvZjgyu4Y4WH2sps8A78197sCduY9vBn4cQjwiUkUlF6ZyyxuvBz5IcN3xScC9\nZnYp8KC7X13ZEEUmax4dLfrXsik3LpIvjNzl7j8AfjBh1x4z2wRcjP4BDF18UTiFp0MZZbT4vwRN\nuXGpC8pLUitGR5uZKjEF41In/grYaGYfcfc91XpQd+8Cuqr1eCISLeVME98A/BnwMeDpCfvvBj5Q\niaBEpnKgpYVip5PHcuMiBUQld70U9VuQKbTQwlRJrmVmk50lWpSXpCa0tBxgqsQUjEud6APeBtxn\nZvvM7NEJ2yNhByci9amcd7fvBVa5+4/N7J8m7L+TYDq4yKxq7+xk5+AgSwuM7cyNixQQeu4ys1bg\nE8BF1Xg8qU2dp3YyeP9g0GMq355gXOqG8pLUhM7OdgYHd0KRd1+dne3VDklmz5qwAxCRxlNOYeoY\n4N4C+5spfipFpGISySSr+vvZkM2yhGDa3xhBUWpdayt9STXglIIqlrvMrAe49BA3O93dBybc55XA\nNuBb7v61qe64Zs0a5s6dO2lfoeVZpT4le5L0n91PlizM42CS2wOtd7aS3KYcV2mpVIpUKjVp3759\n+6rx0DWTl0C5qZElkwn6+1eRzW6AvHdfra3rSCb7wg2wDoWVl9x9y6w/iIhInnIKU4PAG4FU3v7z\nCc7wicyqWCzGlTfeyPv+dAV7d+/GDjyLNx/GsfPn87Xv3KDliqWYSuauK4BrD3Gb3eOf5P75uxW4\nzd0/dKiDb968mcWLF5cYktSLWCxGeluaRE+CHdt2MPTYEAuOWcDy05eT3JZUjpsFhYorAwMDdHR0\nzPZD10xeAuWmRhaLxUin+0gkkuzYsZ6hoWYWLDjA8uXtJJN9ykuzoJp5ycxe5O6Pj38+1W3Hbyci\nUknlFKZ6gC1m9gqCM3rvMLOTgA8B51UwNomAkZERkokEg5kMzaOjHGhpob2zk0QyvH+OhoeHOe/C\n88i+IQsXEPTiHHuW/9nzK8678DzS29J6gzRB/spju/ftZv7c+aGvPBaCHiqUu9x9L9Psx2Jm8wj+\n+bsDWF3K40jjisVi9F7Zy8ADA3Rc3cHWD21l8XEqCNShHpSXpEbEYjF6ezcxMAAdHbB1K6hOWTce\nM7NXuPsw8NgUt3OCXCUiUlElF6bc/UYzezewjiA5fRYYAM7LrfQidWJ4eJgLli1jYzZLklz9B8gM\nDrKqv5++dDgFoO7Lusmelp3cf6UJOB6yZEn0JOi9snfax4ti8a2SJq48Nv5Pbur8VMP9kxtG7srN\nSPgRwSyFBPByMxuP58HZeEwRqR3KS5IvlQo2gP37oa0N1q6FOcG5JOLxYBOpsDOBRyd8LiJSVWUt\n7ePuNwE3VTgWiZhN3d1szGYntblsImh7uSGbJZlIsKl3+gWgSsn8LANnFRmcB5ntmWkfK6rFN5kd\nIeSutwGtwInAfRNDQWccRQTlJZlMhScJg7v/qNDnIiLV0lTuHc3saDM73sxePXGrZHASrsFMhiVF\nxpbkxsMwymhQQSqkKTc+TROLb+OHzC++SX2pZu5y9y3u3uTuzbmP45v++ROR5ygviYiISCMrecaU\nmZ0CbAEKXQeks211pHl0dKr6D82j0y8AVVILLcErrVBwY7nxaRrMZCi2vtUSYH1IxTepPOUuEYka\n5SURERGR8i7l+xeCa5D/BBipbDgSJQdaWqaq/3CgpawrQWes89ROBu8fnNxjatyeYHy6olp8k1mh\n3CUiUaO8JCIiIg2vnMrCycAid/+fSgczU2bWA1yat/tBd39lCOHUvPbOTnYODk7qMTVuZ248DEv/\nMMm3LuvnyXOy8CqCCtIYcD8c9f1Wlv5dsTlQzxfV4lslTWykOvz4ifDA9Xzs1hN5WW4x4AbqZxHZ\n3CUiDUt5SURERBpeOf913w28uNKBVNDdwFsnfH0grEBqXSKZZFV/PxuyWZZwsP6zE1jX2kpfcvoF\noEr68Idj/NmfpUn0JLj5+h3seWqIeUcu4Kw/Wk7y/5a2kl5Ui2+VNLHw9M1b7mVn/zv55Bt38Z4z\nG2tVPqKfu0Sk8dR9XspfZW73bpg/X6vMiUSZmR1BMJPzVcA17v64mc0Dfufuj4cbnYjUo3IKUwlg\nk5ldAvwXQa3iORFIVgfcfTjkGOpCLBajL50mmUiwPpOheXSUAy0ttHd20pcsrQA0G7H1XtnLN28Z\n4ML+Di5/49ayCi1RLb5V2sjISFDIu20HPAXd31nJ9j9aTrIn3J9jlUU9d4lI46n7vDSx8DQwAB0d\nQaFqccOdGxGpDWbWBvyAoGj+AmAb8Djwl8CxwAfCi05E6lU5hantuY/9Bcai0KjzJDN7gODqrDRw\nibvfE3JMNSsWi7GptzfsMGZNlItvlTI8PMyyc5aRPS0L7wIM9owNsWXPEP1n95Pelq6L73Maop67\nRKTxKC+JSNR8Efgh8BHgkQn7rweuDSUiEal75RSmzqx4FJVzOxAH/ht4GbAO6DezRe7+QKiRSWTV\ne/Gt+7LuoCg1sVl8E3A8ZMmS6EnQe2X9fv8TRDl3iUhjUl4Skah5I/A6d3/WbFIX1t8A6tsrIrOi\n5MKUu/9oFuKoCHf/wYQvf2lmK4As8D5gQ6Ufb2RkhGQiwWDeTJtEncy0ibKRkRESiSQ33zoAT7TR\n3Xsx29+8mGQyoec+T+ZnGTiryOA8yGzPVDWesEQ5d4lIY1JeEpEIeprCszVfCTxW5VhEpEGUteSY\nmZ0DfJCgId6fuvseM7sQ+I27/7iSAc6Euz9jZj9n8lyRSdasWcPcuXMn7YvH48QP0YlzeHiYC5Yt\nY2M2S5LgusExIDM4yKr+fvrSDXN5VNUNDw+zbNkFZLMbIffs79k7xpYtGfr7V5FO9+m5n+Dp0acL\nLzsI0JQbr6JUKkVqvBNuzr59+6ry2LWSu6IgdVeK1N3Bz2n/6H7ajm1j7fa1zGkJOhbHT4kTX6SO\nxRIN4330dvx0BzwGK7+3kuWn10YfPeUlkfo0fhJ1x45BoJmVKw+wfHl7LZxEvRn4JPCJ8R1mNge4\nDPheWEGJSH0ruTBlZu8Fvgx8HTgXOCI3dBTwt8DbKhbdDJlZC8FSzOlit9m8eTOLy+jAuam7m43Z\n7KTV3JqApcCGbJZkIlHXl4eFqbt7U64o9fxnP5vdQCKRpLd3U0jRRc/DDz0WdCopVJway41XUaHC\n78DAAB0dHbP6uLWUu6IgvkiFJ6kNk/ronQMYDI0NMVQDffSUl0TqU6GTqENDYwwN1cRJ1IuAW3Mn\n9+cAvcBC4FGgK8S4RKSOlTNjah3wQXe/NndGb1w/cHllwiqPmW0AvktwDXSM4E3dMcC/VPqxBjMZ\niq3XtgRYn2mMy6PCcPMD2yH+yyKjzs0P3F/VeCLvmTlwP4XnDd6fG28Mkc1dlZI/y2n3vt3Mnztf\ns5ykrtV4H726z0sijaiWT6LmZm2eClwAdBCc2vwG8E13fyrU4ESkbpVTmDoB2FFg/xMEZ/jCdBLw\nb8BLCeL5T2C5u99X6QdqHh2d6uoomkdHK/2QNa9SPbleMHQ83HRD8fG2FZUIt24ce+TJ7Pv2HFiZ\nDS4UaSK47vR+YGsrx760NdwAq+cEopu7KmLiLKeBBwbouLqD1PkpFh+nddmlftV4H70TqPO8JNKI\nMplBmOIUdiazvprhlMzdnwS+lttEpE6MX2KcyQwyOtpMS8sBOjujcYlxOYWp+4HXAHvy9i8D7p1x\nRDPg7v+7Wo91oKVlqqujONBSVvuuulXJnlwtLQeY6tq0YFzGzZnTAo/fDv/aDYdnoHkUDrTAM53w\n5GeZ86r3hR1itUQ2d4lI+UYZnbKP3iiRPlGkvCRSh0ZHm5kqMQXj0WRmnwZ+7e7fyNv/XuB4d6/4\nglIiMvsKXWIMYwwORuMS46Yy7nM18AUzOy33dczMzge+QNAnoSG0d3ays8jYzty4HDSxJ9f4n+n8\nnlzT1dnZDlM8+8G4jAuej3vhyV547L9g7y+Dj0/2Avc20vOl3CVSh1poCc5VFDKWG48u5SWROnTw\nJGohkT+J+hFgsMD+QeCjVY5FRCpk8iXGk/8jH7/EOEwlF6bc/XKCPk63AS8gaCx+DfBVd/9iZcOL\nrkQyySWtraQJZv6Q+5gG1rW2kkiG+4ONmsFMhiVFxpbkxqcrmUzQ2noJFHj2W1vXkUxOv8jVCPR8\nBZS7ROpT56mdwbyjQvbkxiNKeak0qRSsWBFsa9dCW1vwcXxf3oKvIqGp8ZOoMeDBAvsfAl5e5VhE\npEKCS4yL/0cejIenrNOI7r7OzDYC7QTFrUF3/11FI4u4WCxGXzpNMpFgfV7PpL4SeyY1gkr25IrF\nYqTTfbkleNczNNTMggXjS/BGepWTUEx8vm6+9W/Z88T9zHvhqzjrzYsb7vlS7hKpP8meJP1n95Ml\nC/M42EdvD7Te2UpyW7RPFCkvTV88HmwiUZdMJujvX0U2u4HgH8HxxLQzd1KwL9wAp/Yb4Axga97+\npRQ/DSAiERf1S4zLnt/u7r8H7qhgLDUnFouxqTeyK/1ESqV7csViMXp7NzEwAB0dsHUrLFZ/56LG\nn69v3jLAhf0dXP7GFO85szGfMOUukfoSi8VIb0uT6EmwY9sOhh4bYsExC1h++nKS22rjRJHykkh9\nqfGTqF8FvmxmhwO35Pa9BfhHYHNoUYnIjES9T3OkGy9I/Wjv7GTn4OCkRXPHqSeXiIjMRCwWo/fK\n3udWo9z6oa1ajVKkAaRSBy/h3L8fdu+G+fNhzpxgX5iz7Gr4JOom4CXAPwNH5PY9A1wB/H1YQYnI\nzHR2tjM4uBOK/Ece9iXGKkxJVSSSSVb197Mhm82b0Bz05OpTTy4RERERKcHEwtN4ASiVqpkCUCS5\n+xjQbWbrgYW53ffoEmOR2hb1S4xVmJKqqGRPrvyzY+PNT6NwdiyKUnelSN0dPGHDj+yHh9u44p61\n9D0UPGHxU+LEF+kJExEREZFArhA1/dWJRCTSJl5inMmsZ3S0mZaWA3R2RuMSYxWmpGoq1ZNLhafS\nxBcdLDwNDEDHJ+CqXTqbKCIiIiKTmdmLgEuBM4FjmNyQxt39xFACE5EZG7/EOIpUmBKpc5phJiIi\nIiLT9HXgdOBfgJG8Ma9+OCLSCFSYEqlzKjyJiIiIyDS9DXiTu+syPhGpmqawAxAREREREZFIGAYe\nDTsIEWksKkyJiIiIiIgIwKeBHjM7IuxARKRx6FI+ERERERERAbgIaAVGzGyIYD35ce7uWj5HRCpO\nhSkREZEISd2VInV3sGLB/tH9tB3bxtrta5nTEqxYED/l4EqbIiIiFXb9FGNqfi4is0KFKRERkQiJ\nL1LhSUREwuHuPWHHICKNR4UpEREROaT8mVy79+1m/tz5msklIlJnzOzlwCrgVcBn3f0RM+sAHnL3\n+8ONTkTqkQpTIiJVkGsiuhP4Q+BUd/95yCGJlGTiTK6BBwbouLqD1PkpFh+ndiO1SnlJRPKZ2XPa\n0wAAIABJREFUWSdwE/AAcBLwFeAR4FxgIaAzECJScVqVLyJGRka4ePVqzj35ZFa89rWce/LJXLx6\nNSMjI2GHJiKVkQT2hB2EiMgEyksiku/zwFXu3g7sn7D/u8DycEISkXqnGVMRMDw8zAXLlrExmyUJ\nGMHyF5nBQVb199OXThOLxUKOUkTKZWbnAG8FVgLnhByOiIjykogU0wG8p8D+hwD9QyIis0IzpiJg\nU3c3G7NZlhIUpSD4wSwFNmSzJBOJ8IITkRnJ9Wm4Gvhz4KmQwxERUV4Skak8DryowP5WguKUiEjF\nqTAVAYOZDEuKjC3JjYtI7TEzA7YAX3b3gZDDERFRXhKRQ7ke+LSZHTa+w8xeAWwC/i20qESkrulS\nvghoHh19bqZUvqbcuIhEh5n1AJce4mavB/4IeCHw2fxDTHXHNWvWMHfu3En74vE48bj6jYrMhlQq\nRSqVmrRv3759IUVTntnOS6Dc1MhSqWAD2L8f2tpg7VqYEyzKSTwebFI5Iealiwn6ST0AHAncDBwP\n/ARYV40ARKTxqDBVpvw/0Lt3w/z55f2BPtDSglP4HeFYblxEIuUK4NpD3GY38LfAGcDTwSSF5/zU\nzK5x99WF7rh582YWL9ZKZyLVUqi4MjAwQEdHR0gRlWVW8xIoNzUyFZ6qL6y85O77zOyNwJsJ+k01\nAbvcffusPrCINDRVPMo08Q/0wAB0dASFqnLer7V3drJzcJClBcZ25sZFJDrcfS+w91C3M7O/ZPLZ\nxXkESzD/b4JfbxGRilBeEpGZyl2+9xSwyN1vAW4JOSQRaRAqTEVAIplkVX8/G7JZlhCclhgjeHe4\nrrWVvmQy3ABFpCzuft/Er83sydynWXf/bQghiUiDU14SkWLc/Vkz+03YcYhI46nL5udm9jEzGzKz\np8zsp2b2hrBjmkosFqMvnea6ri7Oa29nRVsb57W3c11XF33pNLGYVmYVqSMedgAiInmUl0Rk3P8B\nNppZoZX5RERmRd3NmDKzVcDngL8gaNL3YeD7Ztaef5YwSmKxGJt6e8MOQ0Rmkbv/GmgOOw4RkXHK\nSyKS5y+B1wAPmdm9wDMTxtzd1WhORCqu7gpTwEXAVe7+rdzX68zs7cBHgUsq+UAjIyMkEkl27BgE\nmlm58gDLl7eTTCY0y0lERERERGrN9VOMaXaliMyKuipMmdnhwGLgsryhHwLLKvlYw8PDLFt2Adns\nRiAJGENDYwwNZejvX0U63afilIiIiIiI1Ax37wk7BhFpPPXWY+qlBNPRH8zb/xDwiko+UHf3plxR\naikwvtxyE7CUbHYDiYQalouIiIiISG0xs5eb2V+aWdLMXpLb12Fmrwo7NhGpT3U1Y2oKRaedrlmz\nhrlz507aF4/HicfjUx4wkxkkmClVyBIymfWlxijSEFKpFKlUatK+ffv2hRSNiNS61F0pUncHOWX/\n6H7ajm1j7fa1zGmZA0D8lDjxRVP/TRcRkYCZdQI3AQ8AJwFfAR4BzgUWAkqoIlJx9VaYehg4wPNn\nRx1HkFyfZ/PmzSxeXHoPv9HRZg7OlMrXlBsXkXyFCr8DAwN0dHSEFJGI1LL4IhWeREQq6PME/XrX\nmdnvJuz/LvCRkGISkTpXV5fyufszwC7gLXlDbwZur+RjtbQcoPhErLHcuIiIiIiISM3oAK4usP8h\nYNYa6JrZAjP7hpn9xsyeMbP7zOzyXA9hEalzdVWYyvk88FEz+19mdoKZrSdY8vQrlXyQzs52YGeR\n0Z25cRERERERkZrxOPCiAvtbCYpTs+Wk3GNfCCwAPpD7fPMsPqaIRETdFabc/VvAXxM0gPoF8CfA\n2939vko+TjKZoLX1EiANjOX2jgFpWlvXkUwmKvlwIiIiIiIis+164NNmdtj4DjN7BbAJ+LfZelB3\n/4G7f9zdf+zue9z9ptxjvmu2HlNEoqPuClMA7v5ld1/g7nPc/fXu/p+VfoxYLEY63UdX13UsWHAe\nsIIFC86jq+s60uk+YrFZm+kqIlLUyMgIqz++mpXvWgnXwsp3rWT1x1czMjISdmgi0qBGRkZYvfpi\nVq48F1jBypXnsnr1xcpLItF0MfBKgv68RwI3A78B9gPrqhzLS4G9s3Xw8dx08snn8trXruDkk5Wb\nRMJSb83PqyoWi9Hbu4mBAejogK1boYw+6iIiFTE8PMyyc5aRPS0L5wAGQ2NDDO0Zov/sftLb0iqa\ni0hVDQ8Ps2zZBWSzGwkmsxtDQ2MMDWXo71+lk3kiEePu+8zsjQQ9ejsIJjLscvft1YzDzFqBTwAX\nzcbxC+UmGGNwULlJJAx1OWNKRKQRdV/WHRSljufgoqFNwPGQPS1LokeXGItIdXV3b8r947eUyYlp\nKdnsBhKJZHjBiQgAZvaImb009/nXgBe6+y3uvsndL59JUcrMesxs7BDb4rz7vBLYBnzL3b82o2+u\nCOUmkWjRjCkRkTqR+VkGzioyOA8y2zNVjUdEJJMZJJiNUMgSMpn11QxHRAp7ATAXeBjoAtYCv6vQ\nsa8Arj3EbXaPf5IrSt0K3ObuHzrUwdesWcPcuXMn7YvH48Tj8Snvp9wkUrpUKkUqlZq0b9++fRU5\ntgpTEZC6K0Xq7uAHvH90P7v37Wb+3PnMaZkDQPyUOPFFUydXEZFRRg+e9MvXlBsXEami0dFmpkpM\nwbhIfUmlgg1g/35oa4O1a2FO8NaeeDzYImQn8B0zG8h9/QUz2w/4hNsY4O7+vlIO7O57mWafKDOb\nR1CUugNYPZ37bN68mcVl9FJRbhIpXaGi78DAAB0dHTM+tgpTZarkH5z4ooOFp4EHBui4uoPU+SkW\nH6eGVSIyfS20BG8hC73PGsuNi8zAyMgIiZ4EO366Ax6Dld9byfLTl5PsSaoXhxTU0nKAqRJTMC5S\nvpGRERKJJDt2DALNrFx5gOXL20kmE6HlpQgWng7l3QSrms/PfT2XoPH58wpTsxVAbqbUjwhmTyWA\nl5sFecPdH6z04yk3iUSL/kspUw3+wRGROtd5aieD9w8GPaby7QnGRcql5vpSjs7OdgYHdxL0ccm3\nk87O9mqHJHVEzfUrw93vB9YAmNkQ8F53f7jKYbwNaAVOBO6bGB5Q8elLyk0i0aLm5xGQSsGKFcH2\nsfiJcO31fCx+4nP78i7jFBEpKNmTpPXO1uDt3Fhu5xhwH7Te2UqyR408pXxqri/lSCYTtLZeAqSZ\nnJjStLauI5nU60bKpwbWlTGx+TnBrKWnqx2Du29x9yZ3b859HN9m5Zo65SaRaFFhKgLicbjhhmD7\n5KX3wrvfyScvvfe5fZqZJSLTEYvFSG9L03VEFwu2LYBrYcG2BXQd0aXZLDJjmZ9l4FVFBuflxkXy\nxGIx0uk+urquY8GC84AVLFhwHl1d12k2i8xY0MB6SZHRJblxmYbx5ucAf0FwGV9dm5ib2tvPo61t\nBe3tyk0iYdGlfCIidSQWi9F7Ze9z/eq2fmir+tVJRai5vpQrFovR27uJgQHo6ICtW6GMXsUiz6MG\n1hVTqPn5U3m3Kav5eZSN5yYRCZ8KUyIiInJIaq4vIlGjBtYVE3rzcxFpbHoXGRHjK4rcfOsAPNFG\nd+/FbH/z4lBXFBERERmn5voiEjVqYF0Zec3Pf004zc9FpIGpx1QEDA8Pc8YZq9iy5Xz27N4Oe3/J\nnt03s2XL+ZxxxipGRkbCDlFERBqcmuuLSNSogXXlufsJKkqJSLWpMBUBWlFERESiTs31RSRq1Fy/\nMszsL83syAmfF93CjlVE6pMu5YuAYMWQYsWnJWQy66sZjoiISEFqri8iUaPm+hWxBvgm8BRwEVP3\nkvpiVSISkYaiwlQEBCuGPAxHJeDwDDSPwoEWeKYTnkxqRREREREREZkV7r5gwucnhBiKiDQoFabK\nlLorReruFAD7R/eze99u5s+dz5yWOQDET4kTXxSf5tGehBedAf8rC68iuJpvDNgzCN/uB06o/Dcg\nIiIiIiIiIhIyFabKFF90sPA0fklD6vxUWZc0jM15MChKTVzpqIng65VZxn46pyIxi4iIiIiITGRm\nmzl4+Z4xxaV87n5RVYISkYaiwlQENM15NpgpVciroOnuZ6saj4iIiIiINIzTmFyMWkxwmvy/CApV\nJxNcz7Gr+qGJSCNQYSoKWji4GF++JvRTEhERERGRWeHubxr/3MwuAvYCXe7+RG7fC4Fe4CehBCgi\nda8p7AAEWmgpPmF2LDcuIiIiIiIyu/4GuGS8KAWQ+3wd8NehRSUidU2FqQjoPLUT7i8yuCc3LjID\nIyMjXLx6NeeefDIrXvtazj35ZC5evZqRkZGwQ2sIZnaume00syfN7FEz+/ewYxKRxqa8JCJFHA3E\nCuyPAS+qciwi0iA0FScCkj1J+s/uJ0sW5hGUC8eAPdB6ZyvJbcmQI5RaNjw8zAXLlrExmyXJwUUf\nM4ODrOrvpy+dJhYr9P5DKsHMzge+AlwE/Ag4DFgUZkwi0tiUl0RkCt8Bvp67pO8nBNd1nAF8Drgu\nzMBEpH5pxlQExGIx0tvSdB3RxbzrF8C1MO/6BXQd0UV6m4oGMjOburvZmM2ylIOtzJqApcCGbJZk\nIhFecHXOzFqALwCfdPdvuPt97n6vu18fdmwi0piUl0TkED4K9APfBh4AHgS2ArflxkREKk6FqQhI\npeD974+x975eXnXMAHA9rzpmgL339fL+98dIpcKOUGrZYCbDkiJjS3LjMmsWA68E3MzuNLOHzewW\nM+sIOzARaVjKSyJSlLv/3t27gJcRzJRaBsTc/S/c/fehBicidUuX8kVAPB5sAAMP3EvH1e/kqg/t\nYvFxi8MNTOpC8+jolIs+No+OVjOcRnNi7uNG4BME3eQuArab2UJ3fzC0yESkUSkvicghuftjwM6w\n4xCRxlBXM6bM7NdmNpa3bQw7LpEwHWhpmWrRRw60qD5dKjPrKZBr8rcODubYHnf/vrvfBXwA2A+s\nCu0bEJG6o7wkIiIitare/iN14NPAVyfsm7UppyMjIyR6Euz46Q54DFZ+byXLT19OsiepvlASGe2d\nnewcHGRpgbGduXEp2RXAtYe4zW4Orl7zi/Gd7n7AzH5FcClNQWvWrGHu3LmT9sXjceLjUytFpKJS\nqRSpvOvm9+3bF1I0ZZvVvATKTSLVVCd5SURkWuqtMAXwhLsPz/aDDA8Ps+ycZWRPy8I5gMHQ2BBD\ne4boP7tfTcslMhLJJKv6+9mQzbKEg4s+7gTWtbbSl9Sqj6Vy973A3kPdzsx2AU8DbcAduX1NQCvw\nrWL327x5M4sX61JekWopVFwZGBigo6N22i7Ndl4C5SaRaqqHvCQiMl11dSlfzloze8TM/tvMNpjZ\n4bPxIN2XdQdFqeOZvNTZ8ZA9LUuiRyudSTTEYjH60mmu6+rivPZ2VrS1cV57O9d1ddGXVgF1Nrn7\n4wRLsm8wsz82sxOBLwGHA/8aanAi0pCUl0RERCRq6m3G1D8Au4BHgdfnvj4RqPgc88zPMnBWkcF5\nkNmulc4kOmKxGJt6e8MOo1FdDIwSzEQ4hmCy2lnuPhJqVCLSyJSXREREJDIiX5gysx7g0kPc7HR3\nH3D3Kyfs+6WZPQL8h5n9tbv/ttAdy+2XMMooUy11NopWOhMppNF6Jrj7KME/gReHHYuICCgviYiI\nSLREvjDF9Jt5FvLT3MdXAwULU+X2S2ihJWi1Xqg4NZYbF5HnUc8EERERERERGRf56sl0m3kW8brc\nx/srFM5zOk/tZPD+waDHVL49wbiIiIiIiIiIiBQX+cLUdJnZEqAD+BHweO7zK4Dr3b3ihalkT5L+\ns/vJkoV5HFzqbA+03tlKctv0VzpL3ZUidXdwadP+0f20HdvG2u1rmdMyB4D4KXHii7QUs4iIiIiI\niIjUl7opTAHPAF3AZ4EjCS7d+1fg72bjwWKxGOltaRI9CXZs28HQY0MsOGYBy09fTnJbsqSVzuKL\nVHgSERERERERqXUjIyMkEkkymUFGR5tpaTlAZ2c7yWRCK6IXUTeFKXe/E6jq9XOxWIzeK3sZeGCA\njqs72PqhrSw+rvR+VSIiIiIiIiJS24aHh1m27AKy2Y1AkqAp9RiDgxn6+1eRTvepOFVAU9gBiIiI\niIiIiIjUuu7uTbmi1FIOrpTWBCwlm91AIjH9lj+NpG5mTImIiMjsUT9EERERkallMoMEM6UKWUIm\ns76a4dQMFaZERETkkNQPUURERGRqo6PNHJwpla8pNy75dCmfiIiIiIiIiMgMtbQcALzI6FhuXPKp\nMCUiIiIiIiIiMkOdne3AziKjO3Pjkk+FKRERERERERGRGUomE7S2XgKkgbHc3jEgTWvrOpLJRHjB\nRZh6TImIiIiIiIiIzFAsFiOd7iORSJLJrGd0tJmWlgN0draTTPYRi8XCDjGSVJgSEREREREREamA\nWCxGb++msMOoKSpMlUnLZotI1CgviYiIiIhIrVFhqkxaNltEokZ5SUREREREao2an4uIiIiIiIiI\nSChUmBIRERERERERkVDoUj4REREREak5qVSwAezfD21tsHYtzAlaKxKPB5uIiESbClMiIiIiIlJz\nVHgSEakPupRPRERERERERERCoRlTIiIiIjIrdKmViIiIHIoKUyIiIiIyK1R4EhERkUPRpXwiIiIi\nIiIiIhIKFaZERERERERERCQUKkyJiIiIiIiIiEgoVJgSEREREREREZFQqDAlIiIiIiIiIiKhUGFK\nRERERERERERCocKUiIiIiIiIiIiEQoWpCEqlUmGHUJDiKo3iknoS1deN4iqN4pJ6EtXXjeIqjeKS\nehLV143iKo3iqr6aKUyZ2Tozu93MnjSzR4vc5tVmdqOZPWFmI2b2BTM7rNqxzlRUX3CKqzSKSwDM\nbJGZ/cDMfmdmT5lZxszeFnZcpYrq60ZxlUZxCSgvzTbFVRrFJQBm9l0zu8/MnjWzvWb2LTM7Puy4\nShXV143iKo3iqr6aKUwBhwF9wFWFBs2sGfhu7ssO4J3AucDnqhKdiEgeM2sBvg88CZwBLALSwA21\n+GZLRGqf8pKIRNT3gXcB84F3AK8Abgw1IhGpmpopTLl7j7t/Abi7yE3eBrQBXe7+S3e/Hfhr4INm\n9sJqxSkiMsFLgFcCG939bnf/FdANHA68NtTIRKRRKS+JSOS4+5fcfZe7/9bd08DfA39Yi1e/iEjp\naqYwNQ1nAP/X3fdO2HcrcATBDCoRkapy92FgJ7DazI7KzVT4KPAgkAk1OBFpSMpLIhJ1ZvYS4ELg\nFnd/Nux4RGT2tYQdQAW9guBN1XPc/XEzezI3lm8OwD333FOF0Eqzb98+BgYGwg7jeRRXaRTX9E34\nPZwTZhyz5F3ANuB3wBjwEHC2uz9e4LbKSyVSXKVRXNOnvDRJJHNTFF83oLhKpbimr87zEmZ2OfBx\n4Cjgp8A5U9xceakEiqs0imv6KpaX3D20DegheEM01bY47z5dwKMFjnU1cGOB/b8DVhXY/27AtWnT\nFqnt3WHmpErnLoIZmxngOuB04BTg88B9wDzlJW3aamJr6Lyk3KRNWyS3uspLE25/LNAKLAduAW4D\nmpWXtGmriW1Geclyv9ihMLNjCRLQVHa7+9MT7tMFbHb3F+cd6zLg7e7++gn7jgb2AW929x0FHvtP\ngF8D+2fwbYjIzM0BTgBu8smX40bSdHMXQY7ZChzj7k9OuP8gcK27ry9wXOUlkWhQXpp8bOUmkfDV\nZV6a+L/ehPu+jOBqmDe5+4+LHFt5SSR8FclLoV7Klwu8Ukk1Daw1s2MnPCFnAk8Du4o89rUVemwR\nmbnbww5guqabu8zscIIzCGN5Q2MEK40WOq7ykkh0NHxemnBs5SaRaKi7vFSEjR9mimMrL4lEw4zz\nUs30mDKzVxOsJPNqoNnMXkeQsP7H3X8P/AD4JdBrZhfnbvs54Gp3fyKksEWksd0KPAX8s5mtJyiU\nvw/4A+CGMAMTkYalvCQikWJmpxNcatwPPE4w++IzwP8QTD4QkTpXS6vyfQYYILhW+QXAnQQzoToA\n3H0MOJegWDUA3Aj8B/A3IcQqIjJ+Nu9twHHAHcAgcDaw0t2fN5NTRGS2KS+JSAQ9TdAz6naCS/O+\nDfyGoB3LaIhxiUiVhNpjSkREREREREREGlctzZgSEREREREREZE60rCFKTP7mJkNmdlTZvZTM3tD\nyPFcama7cvHsM7PvmdnCMGPKZ2ZrzWzMzDaHHQuAmc0zs2vM7GEz229mPzezjhDjmWNmnzezPWb2\njJndZ2YbzKy5ynH8sZndmItjzMzeWeA2PbnxJ83sVjNrDzMuM2vJPXf/ZWZPm9leM+szs3mzHVeU\nKC+VJ0q5SXmpaBzKSzVKeak8ykuHjCn03KS8VLuUl8qjvHTImJSXyoytErmpIQtTZraKoDF6N/Ba\n4Cbg+2Z2fIhhdQD/ALQDZxA0Jr3FzF4YYkzPMbPXAx8Cfk6R1TGqycxeDNwGPAYsB1qBjwOPhBjW\nZQTXx38AeA3wV7mYqt3n7CiCHmwfz3096edlZt25sdXAImAIuLkKr7Wp4jqK4DlbB5wEnEXQ/2Tb\nLMcUGcpL5YlSblJempLyUg1SXiqP8tK0RCE3KS/VIOWl8igvTYvyUvmxzTw3uXvDbcBO4HN5++4E\nNoYd24R4jiFYuvmtEYjlhQQrHp5JsJrP5yMQ02eBbWHHkRfTd4Gr8vb9K3BNiDGNASsmfG3AA8An\nJ+w7DHgI+FBYcRW5zam5270m7J9tlZ4T5aXS44lUblJemnZMyks1sikvlRWP8tL04opUblJeqp1N\neamseJSXpheX8lKZsRW5TUm5qeFmTJnZ4QTLkf4wb+iHwLLqR1TUS3Mfw64cA1wJ/Ie730LwCxEF\nK4BdZvZtMxsxs1+Y2adCjukG4CwzOwnAzF4HvJFghcioWAC8nAmvf3d/lmB53ii9/iH4HXCCsyl1\nTXmpbFHLTcpL5VFeiiDlpbIpL01P1HOT8lIEKS+VTXlpepSXKquk3NQyu7FE0kuBZuDBvP0PAa+o\nfjjPZ2YGbAb63X0g5FguIKh2vj63K/TL+HJOBC4C/h64lCC+L5vZ0+7+5TACcvf/38xOAH5pZqME\nr7NL3L0vjHiKGH+NF3r9t1Y5lqLMbA7B2ZRvuvvDYcdTBcpLpccTxdykvFQe5aVoUl4qPR7lpWmq\ngdykvBRNykulx6O8NE3KS5VTTm5qxMJUMVH4JR33JeBkIOxGfscDXyCYhvrM+G6iUWlvIkj4n8l9\nfY+ZLSK4djqUhGZmFwF/DvwZMAicBnzRzIbdvTeMmEoQmde/mR1GMG0W4GNhxhIBkfm5EJG8BJHO\nTcpLlRWZ17/y0iSR+bmgvDQdkctLUNO5KTKvf+WlSSLzc0F5aTqUlyorSq//snNTIxamHgYO8Pyq\n+nEE12yGysyuAN4B/LG7/zbkcDqAGDAQFP+BoHL8RjP7OHCE5y4gDcFvgV/k7fsl8BchxDLub4Fu\nd//33Nf/bWbzCZrARSWZjVfYX8Hk6cVRef0fBvQBJwBvdvcnwo2oapSXShPV3KS8VB7lpWhSXiqN\n8lJpop6blJeiSXmpNMpLpVFemqGZ5KaG6zGVqxbvAt6SN/Rm4PbqR3SQmX0JeBdwprvvDjOWnO3A\nKcDrctupwE+Ba4BTQyxKQbCSQ1vevpOA+0KIZdxhBH8sJxrL7Y+KIYKk9tzrP5dA3kD4r//DgG8R\n/Bzf4u6PhhlPNSkvlSyquUl5qTzKSxGkvFQy5aXSRD03KS9FkPJSyZSXSqO8NAMzzU2NOGMK4PPA\nFjP7CXAHB5eE/EpYAZnZVUAceCfwezMbPxPwmLvvDyOmXIVzcOI+M3sSeMTdBwvfq2o2A7flplxu\nJbg2+aME1yuH5Xrg02b2G4KzAKcCf03wC1o1ZvYCgoQw7kQzOxXY6+73mdk/5uL8BXAvcAnwLHBt\nWHERnDnZSjBl9h3AYRN+B/bmGvvVO+WlaYpwblJeKkJ5qWYpL02T8lLJQs9Nyks1S3lpmpSXSqa8\nVGZsVCI3lbo0YL1sBC/+IWA/QVJ7Q8jxjBFUaMfytveG/VzlxRn6EqMTYjkX+DnwdO5n+Vchx3M0\ncBXBVMpngfuBfwAOr3Icb5rw+pn4mvrahNv8XS6BPJX7mbaHGRcwv8jvwAGC6dChv96q9LNTXio/\n1kjkJuWlonEoL9Xoprw0o1iVl4rHFHpuUl6q3U15aUaxKi8Vj0l5qczYKpGbLPcgIiIiIiIiIiIi\nVdVwPaZERERERERERCQaVJgSEREREREREZFQqDAlIiIiIiIiIiKhaNRV+SLNzI4C/iDsOKRu/cLd\nnww7CBEREREREREVpqLpD4BdYQchdasDGAg7CBEREREREREVpiLsmmuuYeHChWGHIXXinnvu4cIL\nLww7DBEREREREZHnqDAVYQsXLmTx4sVhhyEiIiIiIiIiMivU/FxEREREREREREKhGVM1KpUKNoD9\n+2H3bpg/H+bMCfbF48EWtWOLiIiIiIiIiIwzdw87BsljZouBXbt27ZrWpXwDA9DRAbt2QaWv/JvN\nY0t1DQwM0NHRAdDh7mp+Lg3PzH4E3Onua6r8uEPAZnf/YjUfV0SiT3lJRKJGeUmqQTOmRESkUXlu\nq7bTgSene2MzexNwC3CMuz8+W0GJSCQoL4lI1CgvyaxTjympqi1bttDU1PTcduSRR3Lcccdx5pln\n8tnPfpaRkZHn3aenp4empiaam5sZGhp63vjvf/97XvSiF9HU1MTq1aufN/7QQw+xdu1aFi1axNFH\nH82RRx5JW1sbH/nIR/j5z39+yJifffZZLrvsMk444QTmzJnDwoUL+dKXvjTt7/mJJ57gU5/6FPPm\nzePII4/ktNNOo6+vr+BtBwYGeOtb38rRRx/Ni1/8Ys4///yC3/PE53Dilkwmpx2XiITD3fe6+1Nl\n3NUqHoyICMpLIhI9ykuNRYUpCcWWLVv4yU9+wvbt27nqqqs49dRTufzyy1m4cCE//OFZBg3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TbuwQcflCeeeELGjBkjaWlpve1Xr16ViRMnSmhoqFy4cMHqeoqLi22ut6amRjQajWzbts2s/Zln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\n", 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n/zOzEQTd3lvC/Z9ERAqK2i0RiUomyxG8F+jr7lsB3N2Bf5rZ/mb2pru/GnWQ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\nABwi8jGMCTpdl3r+e2cXIiKvAsgE8CMAVSLiOjq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Daxi3dBzcBOOWjqNmaI1KEUhkdIJYJEFbWxu1dbU0Pt9IBx2UUUbVoVXU19WrkxaJQCwW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\nQJvbeuSRR1BXV4ejR9v1LZpUkYGTG7rzzl8B+MTK3E/0811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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#get data DMC for tau=0.002 and compare with tau=0.005 and DFT\n", "smallestSuperCell_DMC_ki_dt0p002=results('DMC', 1, 1, range(12), 0.002)\n", "\n", "\n", "#plot comparison tau=0.005 and tau=0.002 for smallest supercell\n", "method=['DFT','DMC','DMC']\n", "dt=[0.0, 0.005, 0.002]\n", "allRes=[]\n", "allRes.append(smallestSuperCell_DFT_ki)\n", "allRes.append(smallestSuperCell_DMC_ki)\n", "allRes.append(smallestSuperCell_DMC_ki_dt0p002)\n", "\n", "\n", "fig, axs = plt.subplots(ncols=4, figsize=(12, 4))\n", "ax = axs[0]\n", "for m1 in [1,2,0]:\n", " ax.errorbar(range(12),allRes[m1].barrierEnergy(), yerr=allRes[m1].barrierError(), fmt='o',label=method[m1]+' '+str(dt[m1]))\n", "ax.legend(loc='lower center', bbox_to_anchor=(0.5, -0.3), borderaxespad=0)\n", "ax.set_xlabel(\"k point\")\n", "ax.set_ylabel(\"energy [kcal/mol]\")\n", "ax=axs[1]\n", "for m1 in range(1,3):\n", " ax.errorbar(range(12),allRes[m1].barrierEnergy()-allRes[1].barrierEnergy(), yerr=allRes[m1].barrierError(), fmt='o',label=method[m1]+' '+str(dt[m1]))\n", "ax.legend(loc='lower center', bbox_to_anchor=(0.5, -0.3), borderaxespad=0)\n", "ax.set_xlabel(\"k point\")\n", "ax.set_ylabel(\"energy [kcal/mol]\")\n", "ax=axs[2]\n", "for m1 in [2]:\n", " ax.errorbar(range(12),allRes[m1].barrierEnergy()-allRes[1].barrierEnergy(), yerr=sqrt(allRes[m1].barrierError()**2+allRes[1].barrierError()**2), fmt='o',label=method[m1]+' '+str(dt[m1]))\n", "ax.legend(loc='lower center', bbox_to_anchor=(0.5, -0.3), borderaxespad=0)\n", "ax.set_xlabel(\"k point\")\n", "ax.set_ylabel(\"energy [kcal/mol]\")\n", "ax.axhline(0, color='black')\n", "ax=axs[3]\n", "for m1 in [2]:\n", " ax.errorbar(range(12),(allRes[m1].barrierEnergy()-allRes[1].barrierEnergy())/sqrt(allRes[m1].barrierError()**2+allRes[1].barrierError()**2), fmt='o',label=method[m1]+' '+str(dt[m1]))\n", "ax.legend(loc='lower center', bbox_to_anchor=(0.5, -0.3), borderaxespad=0)\n", "ax.set_xlabel(\"k point\")\n", "ax.set_ylabel(\"difference in multibles of errorbar\")\n", "ax.axhline(0, color='black')\n", "plt.suptitle(\"barrier height\")\n", "plt.tight_layout()\n", "\n", "fig, axs = plt.subplots(ncols=2)\n", "ax = axs[0]\n", "for m1 in range(1,3):\n", " ax.errorbar(range(12),allRes[m1].asymtEnergy(), yerr=allRes[m1].asymtError(), fmt='o',label=method[m1]+' '+str(dt[m1]))\n", "ax.legend(loc='lower center', bbox_to_anchor=(0.5, -0.3), borderaxespad=0)\n", "ax.set_xlabel(\"k point\")\n", "ax.set_ylabel(\"energy [kcal/mol]\")\n", "ax = axs[1]\n", "for m1 in range(1,3):\n", " ax.errorbar(range(12),allRes[m1].asymtEnergy()-allRes[1].asymtEnergy(), yerr=allRes[m1].asymtError(), fmt='o',label=method[m1]+' '+str(dt[m1]))\n", "ax.legend(loc='lower center', bbox_to_anchor=(0.5, -0.3), borderaxespad=0)\n", "ax.set_xlabel(\"k point\")\n", "ax.set_ylabel(\"energy [kcal/mol]\")\n", "fig.suptitle(\"asymt\")\n", "plt.tight_layout()\n", "\n", "fig, axs = plt.subplots(ncols=2)\n", "ax = axs[0]\n", "for m1 in range(1,3):\n", " ax.errorbar(range(12),allRes[m1].tsEnergy(), yerr=allRes[m1].tsError(), fmt='o',label=method[m1]+str(dt[m1]))\n", "ax.legend(loc='lower center', bbox_to_anchor=(0.5, -0.3), borderaxespad=0)\n", "ax.set_xlabel(\"k point\")\n", "ax.set_ylabel(\"energy [kcal/mol]\")\n", "ax = axs[1]\n", "for m1 in range(1,3):\n", " ax.errorbar(range(12),allRes[m1].tsEnergy()-allRes[1].tsEnergy(), yerr=allRes[m1].tsError(), fmt='o',label=method[m1]+' '+str(dt[m1]))\n", "ax.legend(loc='lower center', bbox_to_anchor=(0.5, -0.3), borderaxespad=0)\n", "ax.set_xlabel(\"k point\")\n", "ax.set_ylabel(\"energy [kcal/mol]\")\n", "fig.suptitle(\"ts\")\n", "plt.tight_layout()\n", "\n", "#print average over all twist dft, dmc(tau=0.005) and dmc(tau=0.002)\n", "for m1 in range(3):\n", " print method[m1]+' '+str(dt[m1])+': '+str(mean(allRes[m1].barrierEnergy()))+'+/-'+str(sqrt(sum(allRes[m1].barrierError()**2))/len(allRes[m1].barrierError()))" ] }, { "cell_type": "code", "execution_count": 27, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "DFT 0.0: nan+/-nan\n", "DMC 0.005: 12.4167525432+/-0.379371008087\n", "DMC 0.002: 12.2886123839+/-0.538038071209\n" ] }, { "data": { "image/png": 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mz5tZv5k9bGaNUcclIpKhPCUiZWwjsAA4HjgSSAE/M7NjI41KRMalYpbyhX4PvA/YFTgF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\nRU5ErkJggg==\n", 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SJxERkQKqq61j9BOj4QWgIzzYAbwAo58YTV1tXYzRSU+UOImIiBRQZWUlK5evZNaesxi1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\nJzvNq+s3xrQe0cwDyxrTGtjAKQZEO0wsrIwxAdHMA8sa0xr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VqpdFC9mgEyd3vz3l6z+ZWTlB1/fzKbPjiogUBLVZUsrJRaleFi1k2UxHcAAw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\nPuvuv4k2vLfsBqqBh4EWYBl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792e4UOIkIlLkokp4Uus1Pfc0ldecxlXnbKRi/OAGmZdq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\n2+UjIiJw3XXXObYDoEHf6upqFBUVudzOnDlzHNOsWbMM7Q/RlQrEfLF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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#get data DMC for tau=0.002 and compare with tau=0.005 and DFT defEquil\n", "smallestSuperCell_DMC_ki_dt0p002=results('DMC', 1, 1, range(12), 0.002)\n", "\n", "\n", "#plot comparison tau=0.005 and tau=0.002 for smallest supercell\n", "method=['DFT','DMC','DMC']\n", "dt=[0.0, 0.005, 0.002]\n", "allRes=[]\n", "allRes.append(smallestSuperCell_DFT_ki)\n", "allRes.append(smallestSuperCell_DMC_ki)\n", "allRes.append(smallestSuperCell_DMC_ki_dt0p002)\n", "\n", "\n", "fig, axs = plt.subplots(ncols=4, figsize=(12, 4))\n", "ax = axs[0]\n", "for m1 in [1,2,0]:\n", " ax.errorbar(range(12),allRes[m1].barrierEnergy_defEquil(), yerr=allRes[m1].barrierError_defEquil(), fmt='o',label=method[m1]+' '+str(dt[m1]))\n", "ax.legend(loc='lower center', bbox_to_anchor=(0.5, -0.3), borderaxespad=0)\n", "ax.set_xlabel(\"k point\")\n", "ax.set_ylabel(\"energy [kcal/mol]\")\n", "ax=axs[1]\n", "for m1 in range(1,3):\n", " ax.errorbar(range(12),allRes[m1].barrierEnergy_defEquil()-allRes[1].barrierEnergy_defEquil(), yerr=allRes[m1].barrierError_defEquil(), fmt='o',label=method[m1]+' '+str(dt[m1]))\n", "ax.legend(loc='lower center', bbox_to_anchor=(0.5, -0.3), borderaxespad=0)\n", "ax.set_xlabel(\"k point\")\n", "ax.set_ylabel(\"energy [kcal/mol]\")\n", "ax=axs[2]\n", "for m1 in [2]:\n", " ax.errorbar(range(12),allRes[m1].barrierEnergy()-allRes[1].barrierEnergy_defEquil(), yerr=sqrt(allRes[m1].barrierError_defEquil()**2+allRes[1].barrierError_defEquil()**2), fmt='o',label=method[m1]+' '+str(dt[m1]))\n", "ax.legend(loc='lower center', bbox_to_anchor=(0.5, -0.3), borderaxespad=0)\n", "ax.set_xlabel(\"k point\")\n", "ax.set_ylabel(\"energy [kcal/mol]\")\n", "ax.axhline(0, color='black')\n", "ax=axs[3]\n", "for m1 in [2]:\n", " ax.errorbar(range(12),(allRes[m1].barrierEnergy_defEquil()-allRes[1].barrierEnergy_defEquil())/sqrt(allRes[m1].barrierError_defEquil()**2+allRes[1].barrierError_defEquil()**2), fmt='o',label=method[m1]+' '+str(dt[m1]))\n", "ax.legend(loc='lower center', bbox_to_anchor=(0.5, -0.3), borderaxespad=0)\n", "ax.set_xlabel(\"k point\")\n", "ax.set_ylabel(\"difference in multibles of errorbar\")\n", "ax.axhline(0, color='black')\n", "plt.suptitle(\"barrier height\")\n", "plt.tight_layout()\n", "\n", "fig, axs = plt.subplots(ncols=2)\n", "ax = axs[0]\n", "for m1 in range(1,3):\n", " ax.errorbar(range(12),allRes[m1].asymtEnergy_defEquil(), yerr=allRes[m1].asymtError_defEquil(), fmt='o',label=method[m1]+' '+str(dt[m1]))\n", "ax.legend(loc='lower center', bbox_to_anchor=(0.5, -0.3), borderaxespad=0)\n", "ax.set_xlabel(\"k point\")\n", "ax.set_ylabel(\"energy [kcal/mol]\")\n", "ax = axs[1]\n", "for m1 in range(1,3):\n", " ax.errorbar(range(12),allRes[m1].asymtEnergy_defEquil()-allRes[1].asymtEnergy_defEquil(), yerr=allRes[m1].asymtError_defEquil(), fmt='o',label=method[m1]+' '+str(dt[m1]))\n", "ax.legend(loc='lower center', bbox_to_anchor=(0.5, -0.3), borderaxespad=0)\n", "ax.set_xlabel(\"k point\")\n", "ax.set_ylabel(\"energy [kcal/mol]\")\n", "fig.suptitle(\"asymt\")\n", "plt.tight_layout()\n", "\n", "fig, axs = plt.subplots(ncols=2)\n", "ax = axs[0]\n", "for m1 in range(1,3):\n", " ax.errorbar(range(12),allRes[m1].tsEnergy_defEquil(), yerr=allRes[m1].tsError_defEquil(), fmt='o',label=method[m1]+str(dt[m1]))\n", "ax.legend(loc='lower center', bbox_to_anchor=(0.5, -0.3), borderaxespad=0)\n", "ax.set_xlabel(\"k point\")\n", "ax.set_ylabel(\"energy [kcal/mol]\")\n", "ax = axs[1]\n", "for m1 in range(1,3):\n", " ax.errorbar(range(12),allRes[m1].tsEnergy_defEquil()-allRes[1].tsEnergy_defEquil(), yerr=allRes[m1].tsError_defEquil(), fmt='o',label=method[m1]+' '+str(dt[m1]))\n", "ax.legend(loc='lower center', bbox_to_anchor=(0.5, -0.3), borderaxespad=0)\n", "ax.set_xlabel(\"k point\")\n", "ax.set_ylabel(\"energy [kcal/mol]\")\n", "fig.suptitle(\"ts\")\n", "plt.tight_layout()\n", "\n", "#print average over all twist dft, dmc(tau=0.005) and dmc(tau=0.002)\n", "for m1 in range(3):\n", " print method[m1]+' '+str(dt[m1])+': '+str(mean(allRes[m1].barrierEnergy_defEquil()))+'+/-'+str(sqrt(sum(allRes[m1].barrierError_defEquil()**2))/len(allRes[m1].barrierError_defEquil()))" ] }, { "cell_type": "code", "execution_count": 33, "metadata": { "collapsed": false, "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(0.9575631618499756, 0.7485608458518982)\n", "4.92419992829\n", "1.42149407707\n", "2.95451995697\n", "0.852896446242\n" ] }, { "data": { "image/png": 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oECT22L4H2X195OV9T3Hxifj9J+H3n0BZWQOys6sPFCISm0jWofgYOBNYA7wE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\nAAAASUVORK5CYII=\n", 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wlRR14RI2b4Zq1YyR+YoV8P77xj3glopNjOXxso+T0yeneSFdhDNubWtUshH5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\nuX37nt9Jbu6v7z3nnpOdzZAhQzwpI5YcKTnCoi8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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "vals=[]\n", "for i in range(len(smallestSuperCell_DMC_ki.barrierEnergy())):\n", " vals.append((smallestSuperCell_DMC_ki.barrierEnergy()[i]-smallestSuperCell_DMC_ki_dt0p002.barrierEnergy()[i])/sqrt(smallestSuperCell_DMC_ki.barrierError()[i]**2+smallestSuperCell_DMC_ki_dt0p002.barrierError()[i]**2))\n", "\n", "from scipy.stats import shapiro\n", "print(shapiro(vals))\n", "from scipy.stats import probplot\n", "ax=plt.gca()\n", "probplot(np.array(vals), plot=ax)\n", "ax.plot([-3,3],[-3,3], '--')\n", "ax.plot([-3,3],[-3*1.5,3*1.5], '.-')\n", "figure()\n", "x = np.linspace(-4, 4, 100)\n", "plot(x, sum(normpdf(x, val, 0.4) for val in vals))\n", "plot(x, 12*normpdf(x,0,1))\n", "plot(vals, zeros(len(vals)), 'x')\n", "sigma=sqrt(sum((smallestSuperCell_DMC_ki.barrierEnergy()-smallestSuperCell_DMC_ki_dt0p002.barrierEnergy())**2)/len(smallestSuperCell_DMC_ki.barrierEnergy()))\n", "sigmaOfmean=sqrt(sum((smallestSuperCell_DMC_ki.barrierEnergy()-smallestSuperCell_DMC_ki_dt0p002.barrierEnergy())**2)/len(smallestSuperCell_DMC_ki.barrierEnergy())/(len(smallestSuperCell_DMC_ki.barrierEnergy()-1)))\n", "print(sigma*5/3) #*5/3 for zero time step extrap from tay=0.005 to tau=0.002\n", "print(sigmaOfmean*5/3)\n", "print(sigma) \n", "print(sigmaOfmean)" ] }, { "cell_type": "code", "execution_count": 34, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(0.92831951379776, 0.362640380859375)\n", "4.866777755\n", "1.40491772347\n", "2.920066653\n", "0.84295063408\n" ] }, { "data": { "image/png": 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IDhmGtfyJLp/sxaRxH0N5IbCGgh1WZ7vEtNpQY2VjoUAhIiJpUTVq47te4zDGcvonmxEa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\nAAAASUVORK5CYII=\n", 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TDhl+EOIupKgLt7RggTrr3ceFC9Cj4qPoXK0zeX3zuq5TNxQcrObUL13SncQa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\nFEI4QWhgKLtH7qZb9W48Nv8xOod35tAl96ighqG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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#defEquil\n", "vals=[]\n", "for i in range(len(smallestSuperCell_DMC_ki.barrierEnergy_defEquil())):\n", " vals.append((smallestSuperCell_DMC_ki.barrierEnergy_defEquil()[i]-smallestSuperCell_DMC_ki_dt0p002.barrierEnergy_defEquil()[i])/sqrt(smallestSuperCell_DMC_ki.barrierError_defEquil()[i]**2+smallestSuperCell_DMC_ki_dt0p002.barrierError_defEquil()[i]**2))\n", "from scipy.stats import shapiro\n", "print(shapiro(vals))\n", "from scipy.stats import probplot\n", "ax=plt.gca()\n", "probplot(np.array(vals), plot=ax)\n", "ax.plot([-3,3],[-3,3], '--')\n", "ax.plot([-3,3],[-3*1.5,3*1.5], '.-')\n", "figure()\n", "x = np.linspace(-4, 4, 100)\n", "plot(x, sum(normpdf(x, val, 0.4) for val in vals))\n", "plot(x, 12*normpdf(x,0,1))\n", "plot(vals, zeros(len(vals)), 'x')\n", "sigma=sqrt(sum((smallestSuperCell_DMC_ki.barrierEnergy_defEquil()-smallestSuperCell_DMC_ki_dt0p002.barrierEnergy_defEquil())**2)/len(smallestSuperCell_DMC_ki.barrierEnergy_defEquil()))\n", "sigmaOfmean=sqrt(sum((smallestSuperCell_DMC_ki.barrierEnergy_defEquil()-smallestSuperCell_DMC_ki_dt0p002.barrierEnergy_defEquil())**2)/len(smallestSuperCell_DMC_ki.barrierEnergy_defEquil())/(len(smallestSuperCell_DMC_ki.barrierEnergy_defEquil()-1)))\n", "print(sigma*5/3) #*5/3 for zero time step extrap from tay=0.005 to tau=0.002\n", "print(sigmaOfmean*5/3)\n", "print(sigma) \n", "print(sigmaOfmean)" ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "2.2273389864097157" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#mean uncertainty in barrier at a specific k\n", "mean(sqrt(smallestSuperCell_DMC_ki.barrierError()**2+smallestSuperCell_DMC_ki_dt0p002.barrierError()**2))" ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "2.270160644018302" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#mean uncertainty in barrier at a specific k for defEquil\n", "mean(sqrt(smallestSuperCell_DMC_ki.barrierError_defEquil()**2+smallestSuperCell_DMC_ki_dt0p002.barrierError_defEquil()**2))" ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "2.9545199569712697" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sqrt(sum((smallestSuperCell_DMC_ki.barrierEnergy()-smallestSuperCell_DMC_ki_dt0p002.barrierEnergy())**2)/len(smallestSuperCell_DMC_ki.barrierEnergy()))" ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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NwOtRB5HKbpp3E7OWziKjVwZ/OOgP1K5Ru9D91JgWSU6xNLZ/zvf9auB3wMdA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tYrWowxKRwECgPzA0rBtFRABYu3Et975/L8Nm/R/U3oObGz7I9S17Rh1WwsWU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\n15LuQCIiWWoXoOSu9onAM+7+oJm9BbyT5mMrR4pI5JLpk10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v+1eCgTRWunvt\nVO5bRCQTlCNFRMqnHCmppFHNJd/tGf5cn4Z9N0vjvkVEMkE5UkSkfMqRkjK64y0iIiIiIiKSRhpc\nTURERERERCSN1PAWERERERERSSM1vEVERERERETSSA1vERERERERkTRSw1tEREREREQkjdTwFhER\nEREREUkjNbxFRERERERE0kgNbxEREREREZE0+n/nEZkQP4v3ZQAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#look at time step extrap for various k points\n", "smallestSuperCell_DMC_dts_dictList=[]\n", "k=8\n", "dt=np.array([0.011, 0.008, 0.005, 0.0035, 0.002, 0.001])\n", "smallestSuperCell_DMC_dts_dictList.append({'k':k, 'dt':dt, 'results':results('DMC', 1, 1, k, dt)})\n", "k=9\n", "dt=np.array([0.005, 0.0035, 0.002])\n", "smallestSuperCell_DMC_dts_dictList.append({'k':k, 'dt':dt, 'results':results('DMC', 1, 1, k, dt)})\n", "\n", "for i in range(len(smallestSuperCell_DMC_dts_dictList)):\n", " fig, axs = plt.subplots(ncols=3, figsize=(10, 3))\n", " k=smallestSuperCell_DMC_dts_dictList[i]['k']\n", " dt=smallestSuperCell_DMC_dts_dictList[i]['dt']\n", " dtresults=smallestSuperCell_DMC_dts_dictList[i]['results']\n", "\n", " ax = axs[0]\n", " ax.errorbar(dt,dtresults.barrierEnergy(), yerr=dtresults.barrierError(), fmt='o',)\n", " ax.set_xlabel(\"dt [au]\")\n", " ax.set_ylabel(\"barrier energy [kcal/mol]\")\n", " ax.set_xlim(0,max(dt)+0.001)\n", " ax.set_xticks(dt);\n", " labels = ax.get_xticklabels()\n", " plt.setp(labels, rotation=30)\n", "\n", " [popt,pcov]=curve_fit(func,dt,dtresults.barrierEnergy(), sigma=dtresults.barrierError())\n", " [a, erra]=[popt[0], np.sqrt(np.diag(pcov))[0]]\n", " [b, errb]=[popt[1], np.sqrt(np.diag(pcov))[1]]\n", " xmin, xmax = ax.get_xlim()\n", " ax.plot([xmin, xmax], [func(xmin,a,b), func(xmax,a,b)], '--');\n", "\n", " ax=axs[1]\n", " ax.errorbar(dt,dtresults.asymtEnergy(), yerr=dtresults.asymtError(), fmt='o',)\n", " ax.set_xlabel(\"dt [au]\")\n", " ax.set_ylabel(\"asymt energy [kcal/mol]\")\n", " ax.set_xlim(0,max(dt)+0.001)\n", " ax.set_xticks(dt);\n", " labels = ax.get_xticklabels()\n", " plt.setp(labels, rotation=30)\n", " \n", " [popt,pcov]=curve_fit(func,dt,dtresults.asymtEnergy(), sigma=dtresults.asymtError())\n", " [a, erra]=[popt[0], np.sqrt(np.diag(pcov))[0]]\n", " [b, errb]=[popt[1], np.sqrt(np.diag(pcov))[1]]\n", " xmin, xmax = ax.get_xlim()\n", " ax.plot([xmin, xmax], [func(xmin,a,b), func(xmax,a,b)], '--');\n", "\n", " ax=axs[2]\n", " ax.errorbar(dt,dtresults.tsEnergy(), yerr=dtresults.tsError(), fmt='o',)\n", " ax.set_xlabel(\"dt [au]\")\n", " ax.set_ylabel(\"ts energy [kcal/mol]\")\n", " ax.set_xlim(0,max(dt)+0.001)\n", " ax.set_xticks(dt);\n", " labels = ax.get_xticklabels()\n", " plt.setp(labels, rotation=30)\n", "\n", " [popt,pcov]=curve_fit(func,dt,dtresults.tsEnergy(), sigma=dtresults.tsError())\n", " [a, erra]=[popt[0], np.sqrt(np.diag(pcov))[0]]\n", " [b, errb]=[popt[1], np.sqrt(np.diag(pcov))[1]]\n", " xmin, xmax = ax.get_xlim()\n", " ax.plot([xmin, xmax], [func(xmin,a,b), func(xmax,a,b)], '--');\n", "\n", " plt.tight_layout()\n", " plt.suptitle(\"k={}\".format(k))" ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "collapsed": false, "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "DMC normal: 12.3967259682+/-0.376384175\n", "DMC small: 11.1125070296+/-0.45708692501\n", "difference: 1.28421893863+/-0.59210936845\n" ] }, { "data": { "image/png": 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ZL8TL7sWsnU3n7BesO1jVRyLip7w6h5vZDOBIYA4TmsKdc78oQFwi0zKuA2yq\ndS52Zkytcxk0H9XMn7b8KWtn0+ajmkse01SoPip/bxvpd2kfF3fXsf9jutGR4Jly4mRmhwK/Intz\n+VQm1RQRn5VzZ1PVR5Uh/UbnpjvjbHwuzGWHxSru8ZPWmKsM+VQqq4AHgX2BV4FDgWOA+/DmTxGR\nMjLW2bR1t1Zqb62HNVB7az2tu7WWw7pXqo+kLAwMDHDcKcex+vXV9J+RhHOg//Qkq19fzXGnHBfI\niWYls3wSp2ag3Tn3It6olVHn3B+Ay4FvFzI4ESmNsc6m131zHZwD131zHR3XdwQ9aQLVR1ImtMZc\n5cgncXLAi6l/vwwckPr3M8D8QgQlIpIj1UdSFrTGXOXIp3P4w8B7gaeAjcDlZvYGcAnw5wLGJpK3\n9GVSBl6eC1tv5eK75rL/3t6+Sp8NvIqoPpKyoDXmKkc+idO/AmMTu3wJ6AS6gSHg3ALFJRlMHGI/\nb995LF+/XEPsM0hPjG668wk2dp3OZcdvqrjOpoWQKclcdddc1n7L2xfwJFP1kZQFrTFXOab8P+Wc\nuy3t338yswa85vHnUutESZGkjzwJiokL4Pb1QV1dMBbA1QiW3KT/H8W3PkH4xtO54YJNZTF1g+oj\nKRdaY65y5DMdwT7ATOfc8wDOOQc8bWb7mtmbzrmXCx2kBNe4D904hMNeIuX3gqEDAwM0n9rsdcY8\nAzDoH02yuj9J1yld5TBaTHKg+kjKRTlP+yHj5dM5fB3eR9FEH02VifhOI1iqhuojKQtlPu2HpMkn\ncToGuDvD/ruAY6cVjUiBaARL1VB9JGWjjKf9kDT59EabQeaEawY7OmmK+EojWHJX5oMOVB+JSEnl\nkzjdD1wE/POE/RcCm6YdkUgBaARL7oI46GAKVB+JSEnl8+lxBfA7M1sA3In30XQCcDxwUgFjE8nb\ngkMWZB/BsgXee+h7Sx6TFIXqIxEpqSn3cXLO3YPXd+A54OPAecAAcJxz7vf5BmJmf29mvzSzfjMb\nNbPTJ5SvTu1P3+7N93pSOIODgyxZcjktLR8GTqOl5cMsWXK5r2sv2bZ94ae13hSIo6mdo3jfr6uF\n1/7Gt9ikcIpVH+XKzC42s6SZbTOz+83s74p9TRHxVz7TEZhz7gHgnAxlezjnXsszlj2AzcAPgJvx\nHrSkc8BvgCVp+zRPi88GBgZobj6bROJaIAoYyeQoyWQPXV1n0d291peOjw8++CS8HIf/WQa79sDM\nEdheA28r5hC3AAAgAElEQVQ0wWtf48EHzy95TFJ4RayPcrn2WcA3gE/iLSp8IfAbM5vvnHuqWNcV\nEZ8556a0Addn2b8ncNdUz5flXKPAaRP2rQZuyfH1jYDbtGmTk+Jqbf2ig24HLsN2r2tt/aIvcc2b\ntzhLTN42b95iX+KqJps2bXJ4NzyNrgD1QqatFPXRJNfeCHxjwr7NwLUZjm0EXGjO0a619YtuYGBg\nyu/nwMCAa239oquv/5CDxa6+/kO+n6sYMdXWneDYd56rrTvB95+vWOea7s+o9yo/haqT8qksHgeu\nnrBvL6AL+L/TCSbtfJkSpw68xTwHgC3Aj4DaLK9X4lQi8+d/yMFolgRlu5s//0OKq0qVKHEqen2U\n5bq7Am8CH5qw/+vA3RmOb/Teiz846HYNDR+Y0gfAs88+6xoaPpC6SRl96/fYz3MFMaZqOFcQYwry\nudL5mTjVA08DX0h9/1fAvcDvgT2nE0zaNTIlTmfidfacl/rak6o0d8/weiVOJRLUlp2gtoRVkxIl\nTkWvj7Jc952peqpxwv7LgUczHJ9KnDbl9TtYyN/nQp0riDFVw7mCGFOQz5WuUHVSPp3Dk8DJwBVm\n9nngDry+Rqc6516d6vmmcN2fOedud879yTl3O3AqXuX10WJdU3aupmY7b++ONmY0VV560WgbDQ1X\n4K33mt47vJuGhiuJRjVzeCXwqz6aLKTcDjuGnp7enE/qHXtMoM4VxJiq4VxBjCnI5yqGvCazcc49\nZGaL8SqpjcBHnHPbChrZzmN43sySZB5wDsDSpUuZPXv2uH2RSIRIgJd6LzdNTfPp7d1I5kmaN9LU\nNL/UIQGp5Q2619LWFuWOu75M/ytbqN3rQBZ9oJFo1J8O65UsFosRG1vtOWVoaKgk1/apPnoO2A7M\nmbD/AGBr1lfNPB7YF7bPp6/vAU477bSc6qSRkZlMNqOrV56bQp0riDFVw7mCGFMQz1XMOimnxMnM\nNmcpeh1vucJ7zMwA55wryfKuZjYbqMPr75TRypUrafR7tdkKF4220dV1FonENXh3CGMrV25Mteys\n9S22UChER8cKbrozznldYa47Psa5J+j3oRgyffjH43HC4XDBrxWE+sg594aZbQI+CNyWVvQBvNG/\nmZ3/Goy+Bj/dldo5h/OLX/wip+u9Wv8UhE/LFg2vvpC1GnybHa3EmWeHzbWVuFDn0bmmdq4gxhTE\ncxWzTsq1xenWHI/LsZn67cxsT+DgtF1zzewI4HngBeBLwC3AM8DfAl9L7b8l32vK9KW37GzYcDXJ\n5Ezq67ezcOF8texIsRS9PsrRN4HVZnYf8Afg08C7ge9nfYXhtZG3JBi9f1bOF1p0wImsXn0mmVt2\nu1nUenPO5ypUK3EhW5t1Lr3vxTpXUUyng1QhN+D9eE0Vo3hN4GP//i9gFl4z/CAwkvoaA+qynEud\nw32waZPXeS9ob/uPf7fJ0Y778e8CFliFK0XncL834LNAEhjGS57+LstxXufwC3C04/gqbl7TvJzf\ny4GBgdQoo3udN7rIpb7eO+VRRoU6VxBjqoZzBTGmIJ8rnW+j6sphU+LkjyAlTmseXOMWr1nsFq9Z\n7I757iLHpfPcMd9d9Na+NQ+u8TvEilcNiVOu29sSp3bcvObcEyfngjl3T1Dn7an0uYmq4b3q7e11\n737ve1xNaA/H/ru4mtAe7t3vfY/r7e2d8rnGlDRxwnsktl/OJ/UWtqibTmDT+qGUOPkiSIlTuqDG\nVemKlTiVW33kMiVOX8XNb56f1/tayBbUQv1tFPJvLIg/X6HPVaifsVLfq2effdY1NDY4PoXjX3b8\nzfApXENjg+8tTrn2cdoH+JCZvZTDsQbsB+TehV6kwGIxbwMYHoZ582D5cpiV6lYSiXiblKXyr4/6\noemIJr+jEAmkZVctI3FkYvyY+RnAQZAgQVt7Gx3Xd/gV3pSmI1hdrCBECk2JUcVb7XcAeXHAU9Cw\nuYFoZ9TvaEQCqeeBHliUpbAWetb3lDSeiXJKnJxzU54oU6qDWnak1Mq5Pgrd/U4+vOgkop1RjTgV\nyWKEkcmmcfLKfZTXBJgiY5QYieTuc1+I8uWLzvU7DJFAq6FmsmmcvHIfle2dm4iIiFSepiOask9t\nHYD+gUqcREREJDCi7VEaNjfAU4xfanSsf2C7v/0D9aiuSk3sm9TXB3V16pskIiL+CoVCdHd209be\nxh23bqB/W5La3etZ9L6FgegfqMSpSqUnRvE4hMNeIjXVpf1iD8WIPexlYMMjw/QN9VE3u45ZNV4G\nFjk8QmSBMjAREcldKBSi4/qOtLVG1wVmrdEpJ05m9nvgB8BPXPFXIJeAiyzYkRjFt8YJ3xgmdmaM\nxgOC8QsulU31kYiUWj59nP4AXAc8a2b/YWbHFTgmEZFcqT4SkZKacouTc+6fzWwZ8GHgfGCDmT0O\ndAD/7Zx7tsAxiohkpPpIqk1694iBF4bhuXmsemQ5a59V94hSyauPk3NuBLgVuNXM3gF8Bvg34Foz\nuw243jl3e+HCFBHJTPWRVJNx3SPiEL4Ubtg09f6phfa2hO7SPi7urmP/xyovoZtW53Aza8K7yzsL\neBb4ITAHuMXM/tM59/nphygisnOqj8rb4OCgN4rqng2wDZbd0sL69y0k2u7/KCrZufSE7qY742x8\nLsxlh8UC06G7kPLpHP4O4OPAEuDdwC+BCPBb57xlwM1sNXAHoIoqoKrp7kAql+qjyjAwMEDzqc3e\nwq5nAAb9o0lW9yfpOqWL7s5uJU8SGPm0OD0FPIE3kuWHzrmBDMf8Ea/Tpq8u/vXF7P/Y/oASgYmq\n6e5AKlrZ1EeS3bKrlnlJ00FpO2cAB0GCBG3tbXRc3+FXeCLj5JM4neic+/1kBzjnhoD35xVRAb36\n8+ugdqH3TQRY4Gs4gTM4OEhbW5Q77orDK/NY1nE56z/QSDTaNqW7u7Em9g33b4CXoOW2FhYepSZ2\nKYmyqY8ku54HemBRlsJa6FnfU9J4RCaTz6i6SSupIDnrM1v48kV+RxFMAwMDNDefTSJxLRAFjP7n\nR1m9uoeurrPo7l6bU9Izron9VMAgOZokqSZ2KYFyqo8kuxFGMi/oCjAjVS4SEPn0cdqMt24x7PhV\nd6ntdeB/8ZrM7yxIhFIUy5atSCVNx6btnQEcSyJxDW1tUTo6Vuz8PGpiFx+pPqoMNdR4/2OZkqfR\nVLlIQOQzAWYnMBd4EfhtansRaADuBfYF7jCzTxQqSCm8np5e4JgspcekynM4zwM9cGCWwtpUuUjx\nqD6qAE1HNMGWLIX9qXKRgMgnjf9r4Frn3Ljlic3scmCec+4jZvYlYDnw3wWIUYpgZGQmk7WNe+U5\nnEdN7OIv1UcVINoepeuULhIkoBbvln4U6IeGzQ1EO6M7OYNI6eTT4hQBYhn2r8WbP2Xs3+/ONygp\nvpqa7ex4wjHRaKo8h/OMNbFnPo2a2KXYVB9VgFAoRHdnN627tVJ7az2sgdpb62ndrVX9JCVw8kmc\nXgcyrQd1DDCc+ncN8Fq+QRXKd676NkuWXM7g4KDfoQROU9N8oBP2WAL7vAf2PcT7uscSoDNVnsN5\n1MQu/iqb+kgmFwqF6Li+g+u+uQ7Ogeu+uY6O6zuUNEng5NMc8B2gw8yOZsfcKE3ARcDXUt+fDGye\nfnjTM/jKc6z+SS933/0P9PTcoj/ANJdfvoQf/zLMyBnDXh8lI9U03kvNz/+HtrZ4TudRE7v4rGzq\nI6luWmOucuQzHcHVZvYs8Fng0tTuXmCpc+4/Ut//J/AfmV5fUpEkjCZ58qe1fO5z7cRi1/sdUWCs\nuH6FlzRlGA03csYw0e9GcxoNN9bE3tbexobODSRfSlK/T703j1On5nGS4iqr+kiqWlDXmJOpm1Li\nZGY1wJXAf6VVSm/jnNs23cAKwvASg5Z+fvObWwElTmMKOeHcWBN7fGuc8I1h1l2wjsYDVBtIcZVd\nfSQiFWFKfZxSq5BfjvcwpnwcCNu2D/kdRaBoNJyUu7Ktj0SkrOXTx+l3wN/hjVQpDzOAmapb02nC\nOakQ5Vcf+SwW8zaA4WGYNw+WL4dZXlcbIhFvE5HM8vl0vA34lpkdAWwC3kgvdM79ohCBFdQo7L7r\n7n5HEShNRzTRu6V3fB+nMRoNJ+WjrOqjtf9xID23ef+eSoKSnuwMvDwXtt7KqrvmsvZbUz+XEqPc\nXfbvMX76qPfGv7l9lF0+/RqLVu/BLj/yHtZ87NAIqy7Um1lt8kmcvpf6uixLeT5THBTXFjj1g9k6\n9FQnjYaTClFW9dHya7dw7slTf116shPf+gThG0/nhgs2+dqXMKgtV4WMa9WFEVaR6tCd6sN5R57v\ne1DfryAq5I1CMeQzqq4oFZGZ/T1ef4VG4ADgH5xzt044ph34DN5swRuBS5xz2dcGccCf4V2b3sV3\n7vhOMcIuW+mj4e64dQP925LU7l7PovdpNJyUj2LVR7Jzfn94ZVPpcVVDAhbEG4V00+rIYmZ7ANuc\nc9nmjp6KPfDmWvkBcDMT5qM2s2XAJcC5QAJvNM0dZnaIc+6VTCcM3f1OPrzoJKJ3KBHIZGw03E13\nxjmvK8x1x6/j3BOC8YspMlUFro9EAimoiVHQW4kKacqJU2oI8NV4LT/7AAcDT5jZV4FnnHM35hOI\nc64Tb8FOzMb3WDZvxz8B/+qcuz2170K8OavPATJe83NfiPLli87NJ5yKV02/5FK5ilUfiVSDQrZe\nBb2VqJDyaXG6BvgH4GIgfYbEh/EW0ixGRVUPvANvBA0Azrk3zawLaC7SNStaoX7J02fDHR4ZZt6+\n81i+fjmzajQbrpSEH/WRSEXQDXJ+8kmcPgGc5Zz7vZn9Z9r+zcDhhQnrbeakvj4zYf+zQEORrik5\nSJ8NV8QHftRHIlLF8kmc9gGeyLB/JhP6JZXApNf78Q3foOe28dO7RCIRIkqxRQoqFosRG2vzTxka\nKsmks0GqjyRP6jog5SSfxKkXOB6ITdh/JsVbSHOspWkO8ELa/gOArdletMsuK4GFgP7wRIop0w1J\nPB4nHA4X+9J+1Ee+GBwc9NaEvH8DvAQtt7V4a0K2l//gl2rqHyPlL5/EqR1YbWZz8O7qPmJmBwMX\nAIsLGFu6JF7y9EG8ihIz2wVvxuAvZ3tRvnOmiEjZaKf09VHJDQwM0HxqM4kjE3AqYJAcTZLsT9J1\nShfdnd1lnzyJlIspz4HinPsl3ki2f8BrCv8acCSweGzEWz7MbE8zOyI1AzDA3NT3B6WGF38L+IqZ\nLTKzBuD7wJvAmnyvKSLlrVj1UdAsu2qZlzQdxI5lkmYAB0HiyARt7W0+RidSXfKax8k591vgtwWO\n5WjgzrFLAN9M/Xs1cL5zLmpmuwM/xJsA8z7gJOfcq9lOuKpnFWtf8Po4aXTXeBoNJ5WiSPVRUeRb\nJ/U80APZFj+ohZ71PQWKUER2Ju8JMM3sr/A6Zo6bdMk59+d8zuecu5udtIA5564Crsr1nDd8+AYa\nG/WMPBONhpNKUuj6qFjyrZNGGMm8IDfAjFS5iJREPhNgHo7XCpTpr9/h9TMQESm6aqmPaqjxfppM\nydNoqlxESiKfv7YfAi8CJwODhQ1HRGRKqqI+ajqiid4tvV4fp4n6vXIRKY18Eqf3AAucc/9b6GBE\nRKbIl/rIzOqBf8Wb72QO3mS8a4CvOOfeKPT1ou1Ruk7pIkECavE6NYwC/dCwuYFoZ7TQlxSRLPJJ\nnB7G65wtIuI3v+qjg4GXgfPwFh0/HPgvYC+8xcgLKhQK0d3Z7c3j1LmB5EtJ6vep9+Zx6iz/eZxE\n0gV98FI+iVMbsMLMrgD+iHff8xbn3MuFCExEJAe+1EepqQ7SpzvoN7MVwOUUIXECL3nquL6D+NY4\n4RvDrLtgnSaIzGDih27fUB91s+sC86ErOxf0wUv5JE7rU1+7MpRVTGdMESkLQaqP9gOeL+H1JIP0\nD92xJDN2ZkxJphRMPonTCQWPQkQkP4Goj1KT8l4KfMHvWEpFLTtSraacOKXmWxIR8V2h6yMzawe+\nupPDjnLOxdNe806gE/iJc+6/ChlPkKllR6pVXpN/mNmpwGeAA4F/cM71m9l5wJ+dc78vZIAiIpMp\ncH20ip0v49SXdu13AncB9zjnLtjZyZcuXcrs2bPH7cu0QLKITE8sFiMWG7/299DQUEHOnc8EmJ8A\nvgf8N/BhYLdU0R54C+6eVJDIRER2otD1kXPueXLsp2RmtXhJ0x+AJbm8ZuXKlVrNQKQEMt2QxONx\nwuHwtM895UV+gSuBzzjnPgukz1fShbfenIhIqfhSH6Vamu4G/ow3su8dZjbHzOYU65oiEgz5PKp7\nF7Ahw/5X8O7yRERK5V34Ux+dBDQAc4Gn0vZrZLFIhcunxWkL8O4M+5uBJ6YXjojIlPhSHznnVjvn\nZjjnZqa+jm1KmqRqDQ4OsuSSJbSc0QJroOWMFpZcsoTBwcpaDSmfFqcbgW+b2dgz/ZCZHQl8G7i2\nYJGJiOyc6iORABgYGKD51GYSRybgVMAgOZok2Z+k65Quuju7K2aG+3ymI7jOzPYG7gFmAd3A68DX\nnXPfKXB8IiJZqT4SCYZlVy3zkqb0hahnAAdBggRt7W10XN/hV3gFldd0BM65K83sWmA+3lvT65z7\nS0EjExHJgeojEf/1PNADi7IU1kLP+p6SxlNMeSVOAM65V/GG4YqI+Er1kYi/RhgBy1I4I1VeIfLp\nHC4iIiLylhpqvDGlmYymyiuEEicRERGZlqYjmrwxrpn0p8orROWkgCIiUpYmLhg8b995LF+/XAsG\nl5Foe5SuU7pIkIBavGaZUaAfGjY3EO2M+hxh4ShxEhERX6UvGCzlKRQK0d3ZTVt7Gxs6N5B8KUn9\nPvUsPGoh0c5oxUxFAEqcREREpABCoRAd13cQ3xonfGOYdReso/GAylubUX2cRERERHKkxElEREQk\nR0qcREREsqiW9dckd+rjJCIikkE1rb8muVOLk4iISAbj1l8bmxV7bP21I73116T6KHESERHJoOeB\nHjgwS2Ftqlyqjh7VSWDEYt4GMDwMfX1QVwezvDnwiES8TfReiZRCNa2/Jrkrm8TJzNqBr07Y/Yxz\n7p0+hCNFkP5hH49DOOwlB42VNw3ItOm9Eim+t9Zfy5Q8Vdj6a5K7cntU9zAwJ21b4G84IiJSqapp\n/TXJXbklTtudcwNp2/N+ByQiIpUp2h6lYXMDPIW37hqpr0+l1l9rr5z11yR35dbOeLCZbcVrOO0G\nrnDOPeJzTCIiUoEqff21iYsr9w31UTe7Tosr70Q5JU73AhHgT8D+wJVAl5ktcM5t9TUyERGpSJW8\n/lr64spjP1/szFjF/HzFUjaJk3Pu9rRvHzOz04AEcD5wTabXLF26lNmzZ4/bF4lEiGi4UWANDg7S\n1hZlw4ZeYCYtLdtZuHA+0Whb2d/dVbJYLEZsbJhfytDQkE/RiIgUT9kkThM5594wswfxpibLaOXK\nlTRqmFHZGBgYoLn5bBKJa4EoYCSToySTPXR1nUV391olT2mClGRmuiGJx+OEw+GSxiEiUmzl1jn8\nLWZWA7yH7GMepMwsW7YilTQdy/hpeo8lkbiGtjZ1xBwzMDDAccedxerVZ5JM/gr4BcnkL1m9+kyO\nO+4sraMlIlIkZZM4mdk1ZtZsZgea2ZHAWmAf4Ic+hyYF0tPTCxyTpfSYVLmAkkwREb+UTeIEHAz8\nDEgCdwK7Agudc0/5GpUUzMjITCabptcrF1CSKSLil7Lp4+Sc+0e/Y5DiqqnZzmTT9HrlAkoyRUT8\nUk4tTlLhmprmAxuzlG5MlQukJ5mZKMkUESkWJU4SGNFoGw0NV+DNbZo+TW83DQ1XEo22+RdcwCjJ\nFBHxhxInCYxQKER391paW2+mvn4xcBr19Ytpbb1ZUxFMoCRTJLvBwUGWXLKEljNaYA20nNHCkkuW\naLSpFETZ9HGS6hAKhejoWEE8DuEwrFsHmorr7caSTG8ep6tJJmdSXz82j5OSzEozcWmMefvOY/n6\n5VoaI4OBgQGaT20mcWQCTgUMkqNJkv1Juk7poruzW38fMi1KnETK0FsfpCfB/ke9SfLRx9n/0Dqe\n/5vH+NT6T+mDtMKkL40hk1t21TIvaUqfGnkGcBAkSNDW3kbH9R1+hScVQImTSBlK/yC96c44G58L\nc9lhMc49Qc1zUt16HuiBRVkKa6FnfU9J45HKoz5OIiJSMUYYmWymDq9cZBqUOImISF6C2Am7hprJ\nZurwykWmQb9BEhiX/XuMnz7qdYB9c/sou3z6NRat3oNdfuTl9x87NMKqC9XPQyQIgtoJu+mIJnq3\n9GZe/r3fKxeZDiVOEhirLoywCi8xim+NE74xzB0XbKLxAPXbEQmaoHbCjrZH6TqliwQJqE3FNAr0\nQ8PmBqKdWsdRpkeJk0gZisW8DWDg5bmw9VZW3TWXtd/y9kUi3iZSLEHthB0Kheju7KatvY0NnRtI\nvpSkfp96Fh61kGhnVFMRyLQpcRIpQ+mJUXzrE4RvPJ0b1DonJRTkTtihUIiO6zvearled8E6/W1I\nwahzuIiITJk6YUu1UuIkUqaCOKJJqkfTEU2wJUuhOmFLBdMtgUgZCuqIJqke6oQt1UotTiJlaNyI\nprF+JmMjmo70RjSJFNNYJ+zW3Vqp76yHNVDfWU/rbq1K3KWiKXGSQNHjp9z0PNADB2YprE2VS9GZ\n2W5m9oCZjZrZe/2Op9TGOmGv+/k6OAfW/XwdHdd3KGmSiqZHdRIYevyUuyCPaKoyUaAfqLqkSaRa\nqcVJAkOPn3KnEU3+M7NTgROBL/odi4iUjhInCQw9fsqdRjT5y8zeAdwIfBzY5nM4IlJCui2VwNDj\np9xpRJN/zMyA1cD3nHNxM3uXrwGJBEDsoRixh73lDIZHhpm37zyWr1/OrJpZAEQOjxBZUBnLGShx\nksB46/FTpuRJj5/G0bIShWdm7cBXd3LY0cD7gL2Ar008xc6usXTpUmbPnj1uXyQSIaL1caTMRRYE\nKzGKxWLExtalShkaGirIufVJJIGhVc2nRstKFNwqYM1OjukDvgwcB7zuNT695X4z+7Fzbkm2F69c\nuZLGRv0fiRRbphuSeDxOOBye9rmVOBXZxObLvqE+6mbXVWTz5XTp8ZP4yTn3PPD8zo4zs88BV6bt\nqgV+C/wjsLE40YlIUChxKrL05suxloHYmTG1DGSgx09SDpxzT6V/b2avpf6ZcM497UNIIlJCSpwy\niMW8DWB4GPr6oK4OZnmNRONWppfC0uMnKVPZJocQkQqjxCmD9MQoHodw2Euk1DVBRCZyzj0JzPQ7\nDhEpDc3jJCIiIpIjJU4iIiJVSuuDTl3ZPaozs4uBy4E5wB+Bf3LO/V9/oxIRESkvWh80P2WVOJnZ\nWcA3gE8C9wEXAr8xs/kTR7qIiIhMR6XPhj1ufdAxY+uD4q0P2nF9h1/hBVZZJU7AF4AbnHM/SX1/\npZl9CPgscEUhLzQ4OEhbW5QNG3qBmbS0bGfhwvlEo23KwMV3lV6hiwRB0GbDLrSeB3pgUZbCWuhZ\nr/VBMymbxMnMdgUagasmFP0OaC7ktQYGBmhuPptE4logChjJ5CjJZA9dXWfR3b1WyZP4qtIrdBEp\nPq0Pmp+ySZyA/fCG/D4zYf+zeP2dCmbZshWppOnYtL0zgGNJJK6hrS1KR8eKnM83ODjoTep4/wZ4\nCVpua/EmdWzXpI7p1IoiIlI6Wh80P5XwrhR84rmenl68lqZMjqGn5+qcz6XOd7lTK4qISOlofdD8\nlFPi9Bywnbe3Lh0AbM30gnxXIh8Zmclk7ZdeeW7U+U6qQTFXIheR4tD6oPkpm8TJOfeGmW0CPgjc\nllb0AeA3mV6T70rkr9Y/BeHTskXCqy9syflc6nwn1aCYK5GLSHFofdD8lE3ilPJNYLWZ3Qf8Afg0\n8G7g+4W8yKIDTmT16jMZ38dpTDeLWm/O+VzqfCciIkGl9UGnrqxmDk9NQ/DPeB2QHgVOBj5U6Dmc\notE2GhquALrx2i1Jfe2moeFKotG2nM/1Vue7TNT5TkREpKyUVeIE4Jz7nnOu3jk3yzl3dDFmDQ+F\nQnR3r6W19WZq6xbBvodQW7eI1tabpzwVQdMRTZDtyZ4634mIiJQVNXdkEQqF6OhYwU13xjmvK8x1\nx8c494SpN1+q852IiEjlKLsWp3Iz1vmudbdW6jvrYQ3Ud9bTulurpiIQEREpM2pxKgF1vhMREakM\nanESERERyZESJxEREZEcKXHKIBaDk08e5KBDlvCZj58D//5OPvPxczjokCWcfPIgEyZIFhERkSqh\nPk4ZfPCDA3zl681sOT4BBwIG20ZhS/9j7La5ixNP7AbUqVtERKTaqMUpg3Hry43N+j22vtyR3vpy\nIiIiUn3U4pRBIdeXi8V469HewMtzYeutXHzXXPbf29sXiXibiIiIBJ8SpwwKub5cemJ0051PsLHr\ndC47flNek2mKiMjkYg/FiD3s3a0Ojwwzb995LF+/nFk1swCIHB4hskB3q5I/JU4ZvLW+XKbkaYrr\ny6X/EQ+8MAzPzWPVI8tZ+6z+iEVECi2yQHWqFJcSpwyajmiid0uv18dpoimuL5f+RxyPQ/hSuGET\nNKrBSUREpOyoc3gG0fYoDZsb4Cm8deVIfX0qtb5cu9aXExERqUZKnDIo9Ppyg4ODLFlyOS0tHwZO\no6XlwyxZcjmDg4PF+QFERESkKPSoLotCrS83MDBAc/PZJBLXAlHASCZHSSZ76Oo6i+7utVroV0RE\npEyoxanIli1bkUqajmX8pFDHkkhcQ1ubHvuJiIiUC7U4FVlPTy9eS1Mmx9DTc3UpwxERKQgN+5dq\npcSpyEZGZjLZpFBeuYhIedGwf6lWelRXZDU12/EmhcpkNFUuIiIi5UCJU5E1Nc0HNmYp3ZgqFxER\nkXKgxKnIotE2GhquALoZPylUNw0NVxKNasFgERGRcqHEqchCoRDd3Wtpbb2Z+vrFwGnU1y+mtfVm\nTehrKWAAAB37SURBVEUgIiJSZtQ5PINCjxYJhUJ0dKzwllwJw7p1WnJFRESkHClxykCjRURERCQT\nPaoTERERyZESJxEREZEcKXESERERyZH6OBVZLOZtAMPDMG8eLF8Os7x+5kQi3iYiIiLBp8SpyJQY\niYiIVA49qiux2FjzU8AEMa4gxgTBjCuIMUl5COLvThBjgmDGFcSYILhxFULZJE5m9qSZjU7YrvU7\nrqkK6i9TEOMKYkwQzLiCGFOlM7MPm9lGM3vNzF40s5/7HVM+gvi7E8SYIJhxBTEmCG5chVBOj+oc\n8BXgP9L2vepTLCJSxczsTOD7wBeAu4FdgAV+xiQipVFOiRPAK865Ab+DEJHqZWY1wLeBy5xz/5NW\n9IRPIYlICZVb4rTczP4FeA74KXCVc+4Nn2MSkerSCLwTcGa2GTgIeBC43Dm3ydfIRKag0MuLVYty\nSpy+DmwCXgSOTn0/F8j0vzoL4JFHHilZcLkaGhoiHo/7HcbbBDGuIMYEwYwriDGl/f3N8jOOIpib\n+notcCmwBe+R3XozO8w590yG16hOmoIgxgTBjGs6MR3CIbQf0p79gDfJ+9xBfK8KVic553zbgHZg\ndCdbY5bXfihV/s4MZefg9YnSpk2b/9s5ftYzBa6Pwnj1yyjw8bTXzgS2Ap/Pcm7VSdq0BWebVp3k\nd4vTKmDNTo7py7L//tTXvwWenlD2W+Bc4ElgON/gRGRaZgHvwvt7LAe51kd7p/796NhO59x2M3sc\n7xFeJqqTRPxXkDrJUndDZcf+//buPLqq8t7/+PubkJSQobGYJWgT5CL5ARUvw0UZNQxaBkWlKhdr\nKwRREH63gxShthVYKoNgftUWsWjC1VQELYgULhUrg4ui1FAuiAJWU4NIEwriwGjI8/vjnMTMnCRn\nZx+Sz2uts+Ts4Tnfk+x8fPb4mF1L4MunOec+9rseEWkezCwJKATucs79PjgtisApuznOuSf8rE9E\nvOX3EaeQmNlVBA6RbwI+D/77CWC1Ok0i0picc5+b2WLgYTM7QKDDNBWIBV6odWUROe+dFx0n4Aww\nFpgLxBE4NfcC8KCPNYlI8/UzoBhYASQDbwHXOucO+1qViHjuvD1VJyIiItLYzpshV0RERET81iQ7\nTmZ2r5nlm9lJM3vbzPr7XM+vzCwvWM9nZrbOzDr7WVNlZjY9OP5fVgTUcomZ5ZrZv8zslJntMrOe\nPtbT0sweM7ODZnbGzA6Y2cNmFt3IdVxtZmuCdZSY2Y3VLDMzOP+EmW00sy5+1mVmLYI/uz1mdtrM\njpjZcjO7xOu6IoXyqH4iJZMiLY+CNSmT6lFTuPKoyXWczGw0sBC4H/g/BO68+x8zS/WxrJ4EHtjZ\nBegDnAReN7MEH2sqY2a9gLsJPP3Y13O3ZnYBsBU4BlwDdAAmA0d9LGsWgefw3AVcBvwoWNPURq6j\nFfC34GdDpd+Vmd0fnDeOwLhp+cCGRtjOaqurFYGf2QNAR+BaoC2w3uOaIoLyqH4iJZMiNI9AmVTf\nmsKTR34/dM6Dh9i9BSysNO1vwCN+11aunmQCD9AbEgG1JAD7gEHARuAxn+uZC6z3++dSqaa1wKJK\n014Acn2sqQQYWe69EXgA4/8tNy2GwG3zd/tVVw3LdAsud5nfv9tG+Hkoj+peT8RkUiTmUbAuZVI9\naqphmTrnUZM64mRmsQTGkfpzpVl/Bvo2fkU1ujD4X7/3WgB+C/zROfc6gQ3dbyOBPDN70cwOm9le\nM/uxzzW9AlxrZh0BzOzfgQHAGl+rqqg9cBHltn3n3FfAG0TWtg+B7d8R2ItvspRH9RZJmRSJeQTK\npHCqcx6dL48jCNWFBIY+qDxWVCHQpvHLqcrMDMgC3nDO+TqQj5n9J4Hedq/gpEi4xfLfCIz7NQf4\nFYHanjSz0865J/0oyDn3lJldCuwzs2IC29jPnXPL/ainBqXbd3XbfodGrqVGZtaSwF78751z//K7\nHo8pj+peT6RlUsTlESiTwqW+edTUOk418fuPr7zfAN8B/L5ANBX4NYHD82dKJ+P/Hl4UgRCfHXz/\nnpl1JXC9gy9BZWY/BX4AjALeBboDj5tZkXMux4+a6iBitn0zi+HrB0Te62ctPouY3wkRkkcQsZkU\ncXkEyqRwaEgeNbWO07+As1Tdm2tL4Fyrr8zsCeB64GrnXOXx9RpbTyAF2BHY6QQCey0DzGwy8A0X\nPAHcyD6h3BhgQfuAO32opdQvgPudcy8H3+83s3YELjCMlJAq3atrQ8VTLpGy7ccAywmMEzXQOfel\nvxU1CuVR3URiJkViHoEyqUEamkdN6hqn4F5KHjC40qyBwF8av6KvmdlvgJuAQc65mgYubkyvAZcD\n/x58dSMwcHIu0M2nThME7mBJrzStI3DAh1pKxRD4H2B5JcHpkSKfQFCVbfvBcOiP/9t+DIEnbHcE\nBjvnPvWznsaiPKqzSMykSMwjUCbVWzjyqKkdcQJ4DFhqZm8Cf+Xr2zUX+1WQmS0CxgA3AsfNrHQP\n9JhzzpeR0oM97HfLTzOzE8BR59y71a/VKLKArcFD0S8RuKZgEoHrDPyyGvilmRUQ2PvsBtxH4I+v\n0ZhZPIE/9lL/ZmbdgCPOuQNm9v+Cde4FPgR+DnwFPO9XXQT22F8icCrheiCm3PZ/JHixaFOmPApR\nhGZSJOYRKJPqVRPhyiO/bl30+BbESQR6u6cIhFV/n+spIbB3UFLp9UO/f1aV6vT9cQTBOkYQeH7L\n6eDv8Uc+15MILCJwePkrAoO6LgBiG7mOjHLbTvntKbvcMg8Gw+Fk8PfZxc+6gHY1bP9nCZwi8nVb\na6Tfm/Ko/rX6nkmRlkfBmpRJ9agpXHmksepEREREQtSkrnESERER8ZI6TiIiIiIhUsdJREREJETq\nOImIiIiESB0nERERkRCp4yQiIiISInWcREREREKkjpOIiIhIiNRxEhEREQmROk7SIGa2ycyyfPjc\nfDP7r8b+XBGJbMok8VpTHORXGpcLvhrbfwAnQl3YzDKA14Fk59znXhUlIr5TJomn1HGS85Jz7kg9\nV7WwFiIigjKpOdGpOgkrMxtqZsfM7I4a5meYWYmZDTez/zWzk2b2ppldXmm575nZHjM7FTwE/tNK\n8/9hZj8q977EzMab2SozO25mBWZ2W3DepQT27AA+DS6bHc7vLSKRSZkk4aaOk4SNmf0nsBy4wzmX\ne47FHwHuBa4ADgD/Y2atgu1cHWwnB+gI3A/MNrPJ5dav7nD8r4D/BjoF119qZhcCBcD3gsukA22A\nHyEiTZoySbygjpOEg5nZvcCTwA3OuT+GsM6Dzrmtzrn3gXFAMnBjcN5/AWudcwuccweccyuALM4d\nLL9zzr3snDsA/BKIAfo450qAT4PLFDnnipxzX9TtK4rIeUSZJJ5Rx0kaygjsOWUB1zrntoS43pul\n/3DOfQnsAUoPjXcB/lJp+W3AZWYWU0ube8q1eQr4kkD4iUjzoUwST6njJA3lgJ1AEZBZx/XKC8cF\nkiXVTNOFlyLNizJJPKWOk4TD34FBwI1m9kSI6/Qp/YeZJRDYoyvdO9sD9Ku0fF/gfefcV/Ws8Wzp\nx9VzfRE5fyiTxDPqOElDGWDB6wIGAt8L8eFzD5pZPzNLB7KBY8DLwXmPA8PN7D4zSwveifJj4NcN\nqPPj4H+Hm9mFZhbfgLZEJHIpk8RT6jhJQ5XdSeKc209gL2+MmT16jvV+ASwGdgFpwHDn3IlgO28A\ntxG4QPN9YB7wK+fconoX6Vx+sJ0nCBzCD3UvVETOL8ok8ZQ558cDVqW50tNyRSSSKJOkrnTESURE\nRCRE6jiJH3SYU0QiiTJJQqZTdSIiIiIh0hEnERERkRCp4yQiIiISohZ+F9BUBQeH7OR3HSLA3tLb\nqqV5Uh5JBDnv80gdJ+90AvL8LkIE6Ans8LsI8ZXySCLFeZ9H6jh5LDc3l86dO/tdhjRD7733Hnfc\ncYffZUgEUR6JX5pSHqnj5LHOnTvTo0cPv8sQEVEeiYSBLg4XERERCZE6TiIiIiIh0qk6nyxbFngB\nnDoFH30E7dpBy5aBaWPGBF6R2r6INC1eZobySJoSPTncI2bWA8jLy8s75zUFO3ZAz56QlwdeXH7g\ndfsSmXbs2EHPnj0Bejrnzuu7WKRh6pJH4G1mKI+ap6aURzpVJyIiIhIidZykzpYuXUpUVFTZKy4u\njrZt2zJo0CDmzp3L4cOHq6wzc+ZMoqKiiI6OJj8/v8r848ePk5SURFRUFOPGjasyv7CwkOnTp9O1\na1cSExOJi4sjPT2diRMnsmvXLk++Z6Qr/ZmKNHfKpMjQXDKp6X/DCHb48GHGjfsZt9wyAhjJLbeM\nYNy4n1X7Rx6J7S9dupQ333yT1157jUWLFtGtWzfmzZtH586d+fOf/1ztOomJieTk5FSZ/uKLL1Jc\nXExMTAxmVmHe9u3b6dq1Kzk5Odx2222sWrWKP/3pT0ydOpV3332XjIyMsHyf81Hln5VIQ3iZGV7n\nESiTIkGzyCTnnF4evIAegMvLy3PVKSwsdB06DHSwzUGJA+fgrINtrkOHga6oqKja9ULlZfs5OTnO\nzKr9bgUFBS4tLc0lJSW5wsLCsukPPvigMzM3YcIEl5aW5kpKSiqs179/f3f77be7hIQEN27cuLLp\nn332mWvTpo1r166dO3jwYLX1rFy5st7fJZxOnDjRqJ9X+jOtSV5engMc0MNFwN+EXpGbR855mxle\n550yqXqRlElNKY90xMkn99//KB988AjQGyjtoUcBvfngg4eZNm1+RLdfk9TUVBYuXMgXX3zBU089\nVWV+ZmYmBw4cYMOGDWXT9u/fz9atW8nMzKyy/JIlSygsLGT+/PlcfPHF1X7mzTffXGtNpYfxN23a\nxKRJk0hJSSE+Pp5hw4ZRUFBQYdmSkhLmz59Pp06daNmyJRdddBF33nknBw8erLBcRkYGXbt2ZcuW\nLfTt25f4+HjGjx/PRx99RFRUFAsWLGDevHm0a9eOVq1akZGRwb59+zh9+jTTpk3jkksuoVWrVgwf\nPpxDhw5VaPv3v/89AwcO5MILLyQ2NpbU1FSmTJnC559/Xuv3FGkILzPDrzwCZZIyKfzUcfLJ9u3v\nAlfVMPeq4PzIbb82w4YNIzo6mi1btlSZ17FjRwYMGEB2dnbZtOzsbNq3b8/gwYNL947LvPrqq7Ro\n0YIbbrihwXVNmDCB5ORk/vCHP/C73/2Ot99+m9GjR1dYZtKkScyYMYObbrqJV199lUcffZSNGzfS\nt29fjhw5UracmXHo0CEyMzOZMGECGzZsYMqUKWXzf/vb37Jjxw6ys7N57rnn+Pvf/87IkSP5wQ9+\nwMmTJ3n++edZvHgxW7du5c4776xQw4EDBxg1ahTLly9n06ZNzJ49mw0bNpwzjEUawsvM8DOPQJkE\nyqRw0nOcfFJcHM3Xe16VRQXnR277tYmPj6d169ZV9log8MedmZnJxIkTOXbsGImJiTz77LNMmjSp\n2rYKCgpISUkhLi6uwXXdeOONzJkzp+z9kSNH+PGPf0xBQQFpaWns3buXJUuWcN999zF37lwArr76\narp160b37t3JysrioYceAgKnuI8ePcratWu56qqv/4fwj3/8A4CLLrqI5cuXl00vKipi8uTJdO/e\nnSeeeKJs+p49e3j00Uc5evQo3/rWtwCYPn162XznHFdeeSWdOnWiX79+7N69m65duzb4ZyFSmZeZ\n4WcegTIJlEnhpCNOPmnR4iyB073VKQnOj9z2z6XyXlp5t9xyC7GxseTm5rJu3TqKiooYO3Ys4O2F\nhSNHjqzw/jvf+Q4AH3/8MQAbN24E4Ic//GGF5a644gquuOKKKheXtm3btkJAlTdixIgK79PT02ud\nXloDwIcffsjtt99O27ZtadGiBbGxsfTr1w+AvXv3nuNbitSPl5nhdx6BMkmZFD7qOPnkyiu7AG/V\nMPet4PzIbb82x48f58iRIzWe/4+Pj2f06NFkZ2eTnZ3NkCFDSE1NrXbZtLQ0ioqKOHnyZIPrSkhI\nqPA+Ojqwl1tcXAxQdti7TZs2Vda96KKLOHr0aIVprVu3rvGz4uPjq/2smqaX1vDll18yYMAAdu7c\nycMPP8zmzZt5++23efnllwHC8nMQqY6XmeFnHoEyCZRJ4aSOk0/mz59Ghw4/B7YBJcGpJcA2OnR4\ngPnzp0V0+7VZu3YtJSUltd6Sm5mZyc6dO1mzZk21F2CWGjp0KGfPnuWVV17xoNKKSkPnn//8Z5V5\nhYWFXHjhhZ7X8Prrr3Po0CFycnLIzMykf//+9OjRgwsuuMDzz5bmzcvM8DOPQJnUEMqkqtRx8klK\nSgrbti1n7NiVtG9/AzCS9u1vYOzYlWzbtpyUlJSIbr8mBQUFTJ06leTkZO65554al+vduzeZmZmM\nGjWq1gsMx48fT5s2bZg2bRqffPJJtcusXLmywXUDDB48GAjcQVLe7t272bVrV9l8L50+fRqAmJiY\nCtOXLFni+WdL8+ZlZviVR6BMaihlUlW6ONxHKSkp5OQ8WjZ200svhXfsJq/b3717N2fOnKG4uJii\noiLeeOMNcnJyiI2NZdWqVbUeNgZ4+umnq0yrfB1CUlISq1evZsSIEXTv3p0pU6bQu3dvYmNjef/9\n98nNzWX37t2MGjWqwd8nPT2du+++mwULFhAdHc11111HQUEBDzzwAKmpqfzkJz+ptdZwyMjIID4+\nngkTJvDLX/6ShIQEnn/+ed56q6bTHCLh42VmeJ1HoExSJjUOdZykzkovliwdhiA2Npbk5GS6dOnC\njBkzuOuuu6oElJmFdJFldcv06tWLd955h6ysLFasWMG8efM4e/YsqampDBkyhEWLFtWr3eqmP/nk\nk3To0IFnnnmGBQsW8M1vfpNhw4YxZ86cCoemQ/0+da0hJSWFP/7xj0ydOpXRo0eTnJzMTTfdxPLl\ny6sMzlqfGkSaImWSMqkxmRc9VKnbaORejxau0cibp6Y0Grk0TF3yCLzNDOVR89SU8kjXOImIiIiE\nSKfqfLJsWeAFcOoUpKfD9OnQsmVg2pgxgVekti8iTYuXmaE8kqZEHSefeB0UCiIRqQsvM0N5JE2J\nTtWJiIiIhEgdJxEREZEQqeMkIiIiEiJ1nERERERCpIvDfbJs9zKWvRO4zeRU8Sk++uwj2n2zHS1b\nBG4zGXP5GMZ0rf/VlF63LyJNi5eZoTySpkQPwPRInR6AeWgHPX/Xk7y78+jRNvxPhPO6fYlMTemB\nc9IwdX4ApoeZoTxqnppSHulUnYiIiEiI1HGSOlu6dClRUVF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5ciZNmjTiWFNTE01NmtYUyVR7ezvt7e0jju3YsaNQbx/luCVSMqKqmySZy+U3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\nktDa0hloCmzydkgBby+nt5lNAM5yoS+Oa8leYFu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Z0e7+cp6vmdGb6wtlSp60vlBV0+XV4svnf9OXCRKW4cYmRSZcvO4jOdR7DDhx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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#get DMC results for k-points 0 to 12 for smallest supercell for tau=0.005 with small and normal jastrow\n", "smallestSuperCell_DMC_ki_smallJast=results('DMC', 1,1,range(12),0.005,{'Nf':json.dumps([0,0,0])})\n", "\n", "#plot comparison tau=0.005 normal and small Jast for smallest supercell\n", "method=['DMC','DMC']\n", "jast=['normal', 'small']\n", "dt=[0.005, 0.005]\n", "\n", "allRes=[]\n", "allRes.append(smallestSuperCell_DMC_ki)\n", "allRes.append(smallestSuperCell_DMC_ki_smallJast)\n", "\n", "fig, axs = plt.subplots(ncols=2)\n", "ax = axs[0]\n", "for m1 in range(2):\n", " ax.errorbar(range(12),allRes[m1].barrierEnergy(), yerr=allRes[m1].barrierError(), fmt='o',label=method[m1]+' '+str(jast[m1]))\n", "ax.legend(loc='lower center', bbox_to_anchor=(0.5, -0.3), borderaxespad=0)\n", "ax.set_xlabel(\"k point\")\n", "ax.set_ylabel(\"energy [kcal/mol]\")\n", "ax=axs[1]\n", "for m1 in range(0,2):\n", " ax.errorbar(range(12),allRes[m1].barrierEnergy()-allRes[0].barrierEnergy(), yerr=allRes[m1].barrierError(), fmt='o',label=method[m1]+' '+str(jast[m1]))\n", "ax.legend(loc='lower center', bbox_to_anchor=(0.5, -0.3), borderaxespad=0)\n", "ax.set_xlabel(\"k point\")\n", "ax.set_ylabel(\"energy [kcal/mol]\")\n", "plt.suptitle(\"barrier height\")\n", "plt.tight_layout()\n", "\n", "fig, axs = plt.subplots(ncols=2)\n", "ax = axs[0]\n", "for m1 in range(0,2):\n", " ax.errorbar(range(12),allRes[m1].asymtEnergy(), yerr=allRes[m1].asymtError(), fmt='o',label=method[m1]+' '+str(jast[m1]))\n", "ax.legend(loc='lower center', bbox_to_anchor=(0.5, -0.3), borderaxespad=0)\n", "ax.set_xlabel(\"k point\")\n", "ax.set_ylabel(\"energy [kcal/mol]\")\n", "ax = axs[1]\n", "for m1 in range(0,2):\n", " ax.errorbar(range(12),allRes[m1].asymtEnergy()-allRes[0].asymtEnergy(), yerr=allRes[m1].asymtError(), fmt='o',label=method[m1]+' '+str(jast[m1]))\n", "ax.legend(loc='lower center', bbox_to_anchor=(0.5, -0.3), borderaxespad=0)\n", "ax.set_xlabel(\"k point\")\n", "ax.set_ylabel(\"energy [kcal/mol]\")\n", "fig.suptitle(\"asymt\")\n", "plt.tight_layout()\n", "\n", "fig, axs = plt.subplots(ncols=2)\n", "ax = axs[0]\n", "for m1 in range(0,2):\n", " ax.errorbar(range(12),allRes[m1].tsEnergy(), yerr=allRes[m1].tsError(), fmt='o',label=method[m1]+str(jast[m1]))\n", "ax.legend(loc='lower center', bbox_to_anchor=(0.5, -0.3), borderaxespad=0)\n", "ax.set_xlabel(\"k point\")\n", "ax.set_ylabel(\"energy [kcal/mol]\")\n", "ax = axs[1]\n", "for m1 in range(0,2):\n", " ax.errorbar(range(12),allRes[m1].tsEnergy()-allRes[0].tsEnergy(), yerr=allRes[m1].tsError(), fmt='o',label=method[m1]+' '+str(jast[m1]))\n", "ax.legend(loc='lower center', bbox_to_anchor=(0.5, -0.3), borderaxespad=0)\n", "ax.set_xlabel(\"k point\")\n", "ax.set_ylabel(\"energy [kcal/mol]\")\n", "fig.suptitle(\"ts\")\n", "plt.tight_layout()\n", "\n", "#print average over 12 twists dmc(tau=0.005) normal and small Jast (smallest supercell)\n", "for m1 in range(2):\n", " print method[m1]+' '+str(jast[m1])+': '+str(mean(allRes[m1].barrierEnergy()))+'+/-'+str(sqrt(sum(allRes[m1].barrierError()**2))/len(allRes[m1].barrierError()))\n", " \n", "print 'difference: '+str(mean(allRes[0].barrierEnergy())-mean(allRes[1].barrierEnergy()))+'+/-'+str(sqrt(sum(allRes[0].barrierError()**2)+sum(allRes[m1].barrierError()**2))/len(allRes[m1].barrierError()))" ] }, { "cell_type": "code", "execution_count": 22, "metadata": { "collapsed": false, "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "DMC normal: 12.4167525432+/-0.379371008087\n", "DMC small: 11.2037691059+/-0.460591108713\n", "difference: 1.21298343724+/-0.596713106277\n" ] }, { "data": { "image/png": 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ZJ4FngWOAtTlN29x9sJKxiZTS4OAgC05dQOrIFJwKGKRH0qQH0vSc0kNvdy+xWCzsMEVE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\nEKnjJCIiIhIidZxEREREQqSOk4iIiEiIdHK4T5btXsaydwK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dR3RxTDNrIFi3NJij3b0tfBwDfkxQJeIbwB1m9mF37x3gtenEV1gX+BSRbIhs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\nRWJiIsOGDWPx4sWl5iE7nRrkzBWJeaOsUdbUJE3yGyCadFP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deMyAfe7encu4RCS71OMkIpIdDnzEzLrNbJuZ/ZeZTc53UCIyOkqcRESy4zbgLOAk4Bzg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\nD+nASSmllFLKQzpwUkoppZTy0P8DNZjUnS+3y7EAAAAASUVORK5CYII=\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#get DMC results for k-points 0 to 12 for smallest supercell for tau=0.005 with small and normal jastrow defEquil\n", "smallestSuperCell_DMC_ki_smallJast=results('DMC', 1,1,range(12),0.005,{'Nf':json.dumps([0,0,0])})\n", "\n", "#plot comparison tau=0.005 normal and small Jast for smallest supercell\n", "method=['DMC','DMC']\n", "jast=['normal', 'small']\n", "dt=[0.005, 0.005]\n", "\n", "allRes=[]\n", "allRes.append(smallestSuperCell_DMC_ki)\n", "allRes.append(smallestSuperCell_DMC_ki_smallJast)\n", "\n", "fig, axs = plt.subplots(ncols=2)\n", "ax = axs[0]\n", "for m1 in range(2):\n", " ax.errorbar(range(12),allRes[m1].barrierEnergy_defEquil(), yerr=allRes[m1].barrierError_defEquil(), fmt='o',label=method[m1]+' '+str(jast[m1]))\n", "ax.legend(loc='lower center', bbox_to_anchor=(0.5, -0.3), borderaxespad=0)\n", "ax.set_xlabel(\"k point\")\n", "ax.set_ylabel(\"energy [kcal/mol]\")\n", "ax=axs[1]\n", "for m1 in range(0,2):\n", " ax.errorbar(range(12),allRes[m1].barrierEnergy_defEquil()-allRes[0].barrierEnergy_defEquil(), yerr=allRes[m1].barrierError_defEquil(), fmt='o',label=method[m1]+' '+str(jast[m1]))\n", "ax.legend(loc='lower center', bbox_to_anchor=(0.5, -0.3), borderaxespad=0)\n", "ax.set_xlabel(\"k point\")\n", "ax.set_ylabel(\"energy [kcal/mol]\")\n", "plt.suptitle(\"barrier height\")\n", "plt.tight_layout()\n", "\n", "fig, axs = plt.subplots(ncols=2)\n", "ax = axs[0]\n", "for m1 in range(0,2):\n", " ax.errorbar(range(12),allRes[m1].asymtEnergy_defEquil(), yerr=allRes[m1].asymtError_defEquil(), fmt='o',label=method[m1]+' '+str(jast[m1]))\n", "ax.legend(loc='lower center', bbox_to_anchor=(0.5, -0.3), borderaxespad=0)\n", "ax.set_xlabel(\"k point\")\n", "ax.set_ylabel(\"energy [kcal/mol]\")\n", "ax = axs[1]\n", "for m1 in range(0,2):\n", " ax.errorbar(range(12),allRes[m1].asymtEnergy_defEquil()-allRes[0].asymtEnergy_defEquil(), yerr=allRes[m1].asymtError_defEquil(), fmt='o',label=method[m1]+' '+str(jast[m1]))\n", "ax.legend(loc='lower center', bbox_to_anchor=(0.5, -0.3), borderaxespad=0)\n", "ax.set_xlabel(\"k point\")\n", "ax.set_ylabel(\"energy [kcal/mol]\")\n", "fig.suptitle(\"asymt\")\n", "plt.tight_layout()\n", "\n", "fig, axs = plt.subplots(ncols=2)\n", "ax = axs[0]\n", "for m1 in range(0,2):\n", " ax.errorbar(range(12),allRes[m1].tsEnergy_defEquil(), yerr=allRes[m1].tsError_defEquil(), fmt='o',label=method[m1]+str(jast[m1]))\n", "ax.legend(loc='lower center', bbox_to_anchor=(0.5, -0.3), borderaxespad=0)\n", "ax.set_xlabel(\"k point\")\n", "ax.set_ylabel(\"energy [kcal/mol]\")\n", "ax = axs[1]\n", "for m1 in range(0,2):\n", " ax.errorbar(range(12),allRes[m1].tsEnergy_defEquil()-allRes[0].tsEnergy_defEquil(), yerr=allRes[m1].tsError_defEquil(), fmt='o',label=method[m1]+' '+str(jast[m1]))\n", "ax.legend(loc='lower center', bbox_to_anchor=(0.5, -0.3), borderaxespad=0)\n", "ax.set_xlabel(\"k point\")\n", "ax.set_ylabel(\"energy [kcal/mol]\")\n", "fig.suptitle(\"ts\")\n", "plt.tight_layout()\n", "\n", "#print average over 12 twists dmc(tau=0.005) normal and small Jast (smallest supercell)\n", "for m1 in range(2):\n", " print method[m1]+' '+str(jast[m1])+': '+str(mean(allRes[m1].barrierEnergy_defEquil()))+'+/-'+str(sqrt(sum(allRes[m1].barrierError_defEquil()**2))/len(allRes[m1].barrierError_defEquil()))\n", " \n", "print 'difference: '+str(mean(allRes[0].barrierEnergy_defEquil())-mean(allRes[1].barrierEnergy_defEquil()))+'+/-'+str(sqrt(sum(allRes[0].barrierError_defEquil()**2)+sum(allRes[m1].barrierError_defEquil()**2))/len(allRes[m1].barrierError_defEquil()))" ] }, { "cell_type": "code", "execution_count": 63, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "a= 0.972672869191 +/- 0.254733793604\n", "b= 13.1989913186 +/- 1.770361244\n", "[ 2.09817591]\n", "\n" ] }, { "data": { "image/png": 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QOjrg5z+HESOKrkySpOozQJThgAOy8LBkCdx2Wza1tBRdlSRJxbEbZxm23jp7\nENTnPw+DjFySJBkgyvHVrxZdgSRJtcW/pyVJUm5NHyBWrIA77yy6CkmS6kvTBoiU4Oab4WMfy7pj\nPvVU0RVJklQ/mjJA3H8/TJqUNYx83/vgd7+zO6YkSXk0VYCYPx8++1nYait4+WWYMQPuuAMmTiy6\nMkmS6kvTBIjLLoMxY+C+++Dyy+EPf8iuQEQUXZkkSfWnabpxfuITcNZZcOSR8N73Fl2NJEn1rWkC\nxOjRcMIJRVchSVJjyHULIyK2i4ibIuL5iOiMiD27rT89IuZFxNKIeD0i7oqIbVdyzKkR0RERSyJi\ncUTcHBFj+vNmJElSdeRtAzEEmAMcUZpP3dY/DBwGjAImAI8Ct0bEBn0csxU4FxgLfBxYAtweEWvm\nKWzWLPjrX/PsIUmS+itXgEgpzUwpTU0pXd/L+ukppTtTSn9OKT0KTAHeSxYOejvmniml9pTS06V9\nDgbeD5TVN2LOHNhlF/jkJ+HKK/O8G0mS1F8D1gsjIgYDhwMvAQ/m2HWd0r+L+tro6aezUTJbWuCZ\nZ+DXv4bjjutfrZIkKZ+KN6KMiN2BdrLbHS8Bu6WUXilz3wDOB+5OKc3ubbvvfx9+9SsYPhwuuQQO\nOghWb5rmoJIkFW8gPnZvB8YBw4BDgBkRMTGl9EwZ+/4Q+CjQZ8PL66+HqVPhmGNg6NBVLVeSJOVV\n8QCRUnoDeHtkiSMiYgfgQOC0vvaLiAuB3YHtUkoL+tp23Lgp/P73w2hr+8eytrY22roukCSpSbW3\nt9Pe3v6OZYsXL67oa0RK3TtSlLljRCewV0rpxpVsNxf4RUrp9D62+SGwJ7BDSunJPrZrATo6Ojpo\naWnpV92SJDWj2bNn09raCtDaVzOBcuW6AhERQ4HRXRaNiIjxwMLSdDwwA3gRGE7WpXMj4JddjjEL\nuDalNK00fxHQRhYgXo+I9UubvpJSWtqfNyVJkgZW3lsYE8jaOED2DIjzSl9fAUwGWkr/rgu8BtwH\nTEopPdblGCOAtbvMH1461h3dXuvLgB0zJUmqQbkCRErpDvru+rlXGcfYpNt80wzoJUlSo/DDW5Ik\n5WaAkCRJuRkgJElSbgYISZKUmwFCkiTlZoCQJEm5GSAkSVJuBghJkpSbAUKSJOVmgJAkSbkZICRJ\nUm4GCEmSlJsBQpIk5WaAkCRJuRkgJElSbgYISZKUmwFCkiTlZoCQJEm5GSAkSVJuBghJkpSbAUKS\nJOVmgJDgetgkAAAH6ElEQVQkSbkZICRJUm4GCEmSlJsBQpIk5WaAkCRJuRkgJElSbgYISZKUmwFC\nkiTlZoCQJEm5GSAkSVJuBghJkpSbAUKSJOVmgJAkSbkZICRJUm4GCEmSlJsBQpIk5WaAkCRJuRkg\nJElSbgYISZKUmwFCK9Xe3l50CU3Hc159nvPq85zXt7IDRERsFxE3RcTzEdEZEXt2W396RMyLiKUR\n8XpE3BUR25Zx3K9GxNMRsSQiHixnH1WX/8mrz3NefZ7z6vOc17c8VyCGAHOAI0rzqdv6h4HDgFHA\nBOBR4NaI2KC3A0bE54HvAycCHwFuBW6JiA1z1CVJkqps9XI3TCnNBGYCRERP66d3nY+IKWSBYiyw\noJfDHgtclFK6pjT/zYjYFZgMnFRubZIkqboGpA1ERAwGDgdeAh7sY5sWYFa3VbOArQeiLkmSVBll\nX4EoR0TsDrST3e54CdgtpfRKL5uvA6wGvNBt+YvA+r3sswbA3LlzV71YlW3x4sXMnj276DKaiue8\n+jzn1ec5r64un51rVOJ4kVL3pgxl7BTRCeyVUrqx2/IhZB/+w4BDgH2BiSmlZ3o4xgbAn4EtU0qz\nuyw/HjgkpbRZD/vsB/w8d8GSJOlt+6eUfrGqB6noFYiU0hvAU6XZIyJiB+BA4LQeNn8ZWMG7rzZ8\nAPhLLy9xK7A/8AywdBXLlSSpmawBbEz2WbrKKhogejAI6OxpRUppWUR0ADsBN3dZtSNwSy/7LARW\nOTVJktSkflepA5UdICJiKDC6y6IRETEeWFiajgdmkLVhGE7WA2Mj4JddjjELuDalNK206Dzgioi4\nD3iA7LbHKODi/r4hSZI08PJcgZgA3F76OpF9+ANcQdbtsqX077rAa8B9wKSU0mNdjjECWPvtmZTS\nNRGxNnA22a2LPwK7ppSey/1OJElS1fSrEaUkSWpujoUhSZJyM0BIkqTcai5A5B1cKyL2jYhHS4N4\nPRIRe1Wr1kaR55xHxOERcW9E/L00aNqdEbFNNettBP0dRC4ivlAazO66ga6x0fTjd8taETEtIhZE\nxLLSYIG7VqveRpDzd0tExMkR8UzpfL8QEReVGvBrJVY24GUv+2wfER2l78+TEfF/87xmTQWIvINr\nRcTHyZ58+UNgU+BHwDUR8a/Vqbj+9WNAs62AnwAfA8YBjwC3RcSHq1BuQ+jvIHIRsTFwDnA37x7M\nTn3ox++WwcB/kzUK342s7/yXABt4l6kfP+eHA98obT8K+CKwO3DuwFfbEFY24OU7RMQmZI9QuJns\n+3MS8J8RsU+5L1hTjSgj4vfAb1NKx3VZNge4JaX0rsG1ImI6sHpKad8uy64DlqSU9qtGzfUu7znv\nYf8geyjYiSmlSweu0sbRn3MeEasBdwGXAtsBa6WU9q5GvY2gH79bDgeOBLZItfRLso7045xPA0ak\nlD7dZdl3gU+klLzKmUNvT4vuts33gE+mlFq7LDsf2CqlVNZ4VDVzBaKfg2tN7GH72/vYXl1UaECz\nNYH3AosqWFrDWoVzPhV4IaV0OfDu4XDVq36e8z3IHrhzSelS+lMRcUYpyGkl+nnOZwBbRsSWpWOM\nILv6c8NA1dnkPk7Pn59blvtzPtBPosyjP4Nrrd/D9i/0sb3eqT/nvLvvko1pMqOCdTWy3Oe8dN/4\nILJbRpBdmvSv4vL15+d8BNlTcS8je1ruKODHwHvILrGrb7nPeUrplog4Fbg3IhLZ59NFKaWzB7LQ\nJvZ+ev78XJ3s+/fiyg5QM1cg+pD3F6W/WFddWecwIr4OfB7YJ6W0bGBLang9nvOI+CfgKuDQlNLb\nV3kCr0JUQl8/54OA51NKR6SUHkkp3UA2ps+h1SmtYfV6ziPis8C3ycLy5mTtHz5dChWqjlyfn7V0\nBaI/g2v1dLXhA7w7Valn/TnnwP+OmvoNYKeU0sMDU15DynvOR5I9Ev6mrLkJUAr+EbEc2DSl9PTA\nlNow+vNzvgB4vduyecBaEfHelNKSypbYcPpzzr8BXJxSuqo0/3hErAn8NCK+nVLqcVwl9dsLZN+P\nrj4AvEX2/VupmrkCUfoL9u3Btbrakd4H/7i3h+0nAfdUtrrG1M9zTkScAJwC7NJ1KHatXD/O+Vyy\nv8bGlabxwI1k9yrHkd0+Uh/6+XN+D+8c+4fS/CLDw8r185y/hyx0dNVZWl4zn1UN5F6yz8uuJgEP\npJS6fx96llKqmQn4HPAG8FmyblNnAK8CG5bWXwmc2WX7jwPLyMbg2Iis+8qbwISi30u9TP04518n\nG0p9H7K/Lt6ehhb9XuplynvOe9j/CuC6ot9HPU39+Dn/ELCYrNvsJmQfhAuAM4p+L/Uy9eOcn0E2\nMOM+pfO/A9lVnxuKfi/1MAFDyf7AGE8WvI4pff32+T4L+GmX7TcG/k5222ijLt+vvct+zaLfdA8n\nYTLwdOlD6gFg2y7r/h9wWbft9yX7K+1NsmcS7FX0e6i3Kc85L223ovQD2nWaWvT7qKcp7895t30v\nJxvVtvD3UU9TP363TCT7K21pKTycDgwq+n3U05Tzd8vqwJnAs8ByskZ8l5J1WS78vdT6VApcb/8+\n7vo7+rLS+suB27vtsx3ZlaKlwJPAYXles6aeAyFJkuqD95UkSVJuBghJkpSbAUKSJOVmgJAkSbkZ\nICRJUm4GCEmSlJsBQpIk5WaAkCRJuRkgJElSbgYISZKUmwFCkiTl9v8Bo/6j8oFwPC0AAAAASUVO\nRK5CYII=\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#linear regression\n", "[popt,pcov]=curve_fit(func,smallestSuperCell_DFT_ki.barrierEnergy()-smallestSuperCell_DFT_conv.barrierEnergy(),smallestSuperCell_DMC_ki_smallJast.barrierEnergy(), sigma=smallestSuperCell_DMC_ki_smallJast.barrierError())\n", "[a, erra]=[popt[0], np.sqrt(np.diag(pcov))[0]]\n", "[b, errb]=[popt[1], np.sqrt(np.diag(pcov))[1]]\n", "ax=plt.gca()\n", "xmin, xmax = ax.get_xlim()\n", "plt.plot([xmin, xmax], [func(xmin,a,b), func(xmax,a,b)], '--');\n", "print 'a=',a,'+/-',erra\n", "print 'b=',b,'+/-',errb\n", "print corrDft*a\n", "print" ] }, { "cell_type": "code", "execution_count": 64, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "mean change for ts energy (small jast - large jast): 11.7104530578 +/- 0.415947813351\n", "mean change for asy energy (small jast - large jast): 12.9946719964 +/- 0.421403513007\n" ] } ], "source": [ "#analysis of changes\n", "print 'mean change for ts energy (small jast - large jast):',mean(allRes[m1].tsEnergy()-allRes[0].tsEnergy()),\"+/-\",sqrt(sum(allRes[m1].tsError()**2+allRes[0].tsError()**2))/len(allRes[m1].tsError())\n", "print 'mean change for asy energy (small jast - large jast):',mean(allRes[m1].asymtEnergy()-allRes[0].asymtEnergy()),\"+/-\",sqrt(sum(allRes[m1].asymtError()**2+allRes[0].asymtError()**2))/len(allRes[m1].asymtError())" ] }, { "cell_type": "code", "execution_count": 23, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "mean change for ts energy (small jast - large jast): 11.7489656227 +/- 0.419501786776\n", "mean change for asy energy (small jast - large jast): 12.96194906 +/- 0.424363973605\n" ] } ], "source": [ "#analysis of changes defEquil\n", "print 'mean change for ts energy (small jast - large jast):',mean(allRes[m1].tsEnergy_defEquil()-allRes[0].tsEnergy_defEquil()),\"+/-\",sqrt(sum(allRes[m1].tsError_defEquil()**2+allRes[0].tsError_defEquil()**2))/len(allRes[m1].tsError_defEquil())\n", "print 'mean change for asy energy (small jast - large jast):',mean(allRes[m1].asymtEnergy_defEquil()-allRes[0].asymtEnergy_defEquil()),\"+/-\",sqrt(sum(allRes[m1].asymtError_defEquil()**2+allRes[0].asymtError_defEquil()**2))/len(allRes[m1].asymtError_defEquil())" ] }, { "cell_type": "code", "execution_count": 65, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 65, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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io8NjRUREpIuLpM+GFBbNvSAiInHKegZRM9se2D18+Ep7S71LfDT3goiIxKnDyYaZ9QZm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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, axs = plt.subplots(ncols=2)\n", "ax = axs[0]\n", "for m1 in [1]:\n", " ax.errorbar(range(12),allRes[m1].barrierEnergy()-allRes[0].barrierEnergy(), yerr=sqrt(allRes[m1].barrierError()**2+allRes[0].barrierError()**2), fmt='o',label=method[m1]+' '+str(jast[m1]))\n", "ax.legend(loc='lower center', bbox_to_anchor=(0.5, -0.3), borderaxespad=0)\n", "ax.set_xlabel(\"k point\")\n", "ax.set_ylabel(\"energy [kcal/mol]\")\n", "fig.suptitle(\"asymt\")" ] }, { "cell_type": "code", "execution_count": 66, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2.39176724581\n", "0.690443731603\n" ] } ], "source": [ "sigma=sqrt(sum((smallestSuperCell_DMC_ki.barrierEnergy()-smallestSuperCell_DMC_ki_smallJast.barrierEnergy())**2)/len(smallestSuperCell_DMC_ki.barrierEnergy()))\n", "sigmaOfmean=sqrt(sum((smallestSuperCell_DMC_ki.barrierEnergy()-smallestSuperCell_DMC_ki_smallJast.barrierEnergy())**2)/len(smallestSuperCell_DMC_ki.barrierEnergy())/(len(smallestSuperCell_DMC_ki.barrierEnergy()-1)))\n", "print(sigma) \n", "print(sigmaOfmean)" ] }, { "cell_type": "code", "execution_count": 67, "metadata": { "collapsed": false, "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "a= 2.73458406985 +/- 0.337013334079\n", "b= 12.7641242176 +/- 1.13694522485\n", "\n", "method\t av. over k \t corr. from DFT \t sum \t uncert. from a \t stat. uncert.\n", "DFT\t9.42778347452 \t[ 0.92847194] \t[ 10.35625542] \t0.0 \t\t0.0\n", "DMC\t10.8064690772 \t[ 2.53898459] \t[ 13.34545366] \t[ 0.31290743] \t0.743315949788\n", "[ 0.80649219]\n" ] }, { "data": { "image/png": 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CjEhdNBERkY1zdx5971GGTxnOR999xMDOA7mq11Xs2qzGrZ4kDcJsDja20uNnzawdwQZh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\n2fDYz7BxUWfJdGa2s5nda2bfmtlKM3v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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#get results for 4x4 superce (use results from next cell for paper!)\n", "largestSuperCell_DFT_ki=results('DFT', 2, 2, range(7), 0.0)\n", "largestSuperCell_DMC_ki=results('DMC', 2, 2, range(7), 0.005)\n", "\n", "#plotting\n", "plt.errorbar(largestSuperCell_DFT_ki.barrierEnergy()-smallestSuperCell_DFT_conv.barrierEnergy(),largestSuperCell_DMC_ki.barrierEnergy(), yerr=largestSuperCell_DMC_ki.barrierError(), fmt='o')\n", "plt.xlabel(\"barrier energy DFT(k) - DFT(k point converged)\")\n", "plt.ylabel(\"barrier energy DMC(k)[kcal/mol]\");\n", "\n", "#linear regression\n", "[popt,pcov]=curve_fit(func,largestSuperCell_DFT_ki.barrierEnergy()-smallestSuperCell_DFT_conv.barrierEnergy(),largestSuperCell_DMC_ki.barrierEnergy(), sigma=largestSuperCell_DMC_ki.barrierError())\n", "[a, erra]=[popt[0], np.sqrt(np.diag(pcov))[0]]\n", "[b, errb]=[popt[1], np.sqrt(np.diag(pcov))[1]]\n", "ax=plt.gca()\n", "xmin, xmax = ax.get_xlim()\n", "plt.plot([xmin, xmax], [func(xmin,a,b), func(xmax,a,b)], '--');\n", "plt.savefig(\"kpoints4x4.svg\")\n", "print 'a=',a,'+/-',erra\n", "print 'b=',b,'+/-',errb\n", "print\n", "\n", "#means and corrections over k-points for DFT, DMC, smallest supercell\n", "#correction for DMC scaled by factor a from linear regression\n", "dftNoCorr=sum(largestSuperCell_DFT_ki.barrierEnergy()*largestSuperCell_DFT_ki.weight())/sum(largestSuperCell_DFT_ki.weight())\n", "dmcNoCorr=sum(largestSuperCell_DMC_ki.barrierEnergy()*largestSuperCell_DMC_ki.weight())/sum(largestSuperCell_DMC_ki.weight())\n", "corrDft=smallestSuperCell_DFT_conv.barrierEnergy()-dftNoCorr#mean(largestSuperCell_DFT_ki.barrierEnergy())\n", "corrDmc=corrDft*a\n", "errCorrDmc=corrDmc*erra/a\n", "statErrDmc=np.sqrt(sum((largestSuperCell_DMC_ki.barrierError()*largestSuperCell_DMC_ki.weight())**2))/sum(largestSuperCell_DMC_ki.weight())\n", "print 'method\\t av. over k \\t corr. from DFT \\t sum \\t uncert. from a \\t stat. uncert.' \n", "print 'DFT\\t', dftNoCorr, '\\t', corrDft, '\\t', dftNoCorr+corrDft, '\\t', 0.00000, '\\t\\t',0.00000 \n", "print 'DMC\\t', dmcNoCorr, '\\t', corrDmc, '\\t', dmcNoCorr+corrDmc, '\\t', errCorrDmc, '\\t',statErrDmc \n", "dmc4x4=dmcNoCorr+corrDmc\n", "errDmc4x4=sqrt(errCorrDmc**2+statErrDmc**2)\n", "print errDmc4x4" ] }, { "cell_type": "code", "execution_count": 68, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "a= 2.74379654156 +/- 0.344596985482\n", "b= 12.9119331286 +/- 1.16932642736\n", "\n", "method\t av. over k \t corr. from DFT \t sum \t uncert. from a \t stat. uncert.\n", "DFT\t9.42778347452 \t[ 0.92847194] \t[ 10.35625542] \t0.0 \t\t0.0\n", "DMC\t10.7973608168 \t[ 2.54753811] \t[ 13.34489893] \t[ 0.31994863] \t0.738484613355\n", "[ 0.80481467]\n" ] }, { "data": { "image/png": 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a8wiKiS+BXu7+YxLXFJEGYOnKpYyYMoKOt3Xk6ilXs+CHBXGdN3ToDZSXX08w\n2+Xa4epaMVQkjERueWxJMKFVXb4GQi9f7u5TWH+BoxufIrKO1VWrua/sPq6ecjWLly/mT93/xGUH\nXcYWG8f3qyhYEbSuoqE7M2Zcl7KsIg1dIgVFM4KWgrqsTvD1RERCcXeenfssQycN5YNvPuC0Lqdx\n7aHX0n7z9gm9TjIrhtZcWGy33WDYsNoXFhNpDBItAB4ws9qmu3ZAy5eLSL0oer2IYS8Po0+HPjx6\nwqPsu+2+oV4nmRVDVTCIrCuRguIh6v7JA/geqJcRHiLSuA3oMoB92u3DUblH1TVVf1y0YqhI6iQy\n9fbANOYQEYnb9pttz/abbZ/06xQVFTJ16smUl48k6PfdhGC+vumxFUPHJX0NkcYikVEeIiINytoV\nQwcOfJoOHfoCx9KhQ18GDnyakhKtGCqSCHWiFJGMUuVVPDLrEQ7Z+RB2bFPnRLgpoxVDRVJDLRQi\nkjFeKn+JvLvzOP2Z0xn/4fio44hIAlRQiEjk3vnqHX4z9jccOfZIWrVoxRtnvsFF3S6KOpaIJCDh\nWx5m1kqzU4pIKnz+/edcMfkKHnrnIXbdcleePulpjt/j+KRGbohINML0ofjazJ4A7nf3qakOJCKN\nw/wl89l99O60btGa0UeP5py8c2jetHnUsUQkpDAFRQEwCJhkZvMIli5/0N2/TGkyEWnQdmyzI/f0\nvYdjdz+WzTbaLOo4IpKkhPtQuPuz7n4CsANwJ0GB8ZmZ/dfM+pmZRo6ISFwGdBmgYkKkgQjdKdPd\nK919lLt3AS4F+gBPAAvM7Hoz2zRVIUVERCSzhW5NMLN2wBnAQKA98CRwP9AOuAzoBhyefEQRyUYf\nfvMhH3zzAcftcVzUUeqkBb5EUifMKI9+BH0ojgLeB24HHnH376o9ZzowJ1UhRSR7fL30a6559Rru\nKb2Hvbbei76796WJZeYIdRUMIqkTpoXiAaAY6Onub9bxnC+B60OnEpGs8+PKH7m55GaK3iiiWZNm\n/OPwf3BRt4sytpgQkdQKU1Bsu6F5KNx9GTAiVCIRySprqtbwwNsPcNUrV7Fo2SL+2O2PDO81nC03\n3jLqaCJSj8IUFE3NrLZu2Q6scPeVSWYSkSxy0pMn8fScpzl171O57tDr6LBFh6gjiUgEwhQUiwmK\nh5pT2TlgZjYfeBC4xt3XJJlPRDLc4B6Dueygy9hvu/2ijiIiEQpTUAwERgL3AGv7UOwPnA38FdgC\nGA60AIa/b0uHAAAgAElEQVQlH1FEMtlBOx0UdQQRyQBhCorTgIvcvfpSgBPN7G3gEnfvY2afAaNQ\nQSEiItIohOl+fSDwdi37ZwE9Y4/fALYOG0pEMsPy1cu5t/Re1lTp7qWIrF+YguILgtsbNZ0JzI89\nzgEWhQ0lItGq8ioemfUIe4zegwv+ewHTv5gedSQRyXBhbnn8GXjSzP6PoA+FAfsBXYD+sefsD4xL\nSUKRRqzmTI7z5kH79umdyXFyxWSGvDSEsgVlHL/H8bww4AV2b7t7ai8iIg1OwgWFu483s64ErRSd\nCEZ3vAac4e6zY8+5J6UpRRqp6gVDWRnk5wcFRl5e6q/13sL3KHypkOc/fp4eO/Rg6qCp6nApInFL\nqKAws+bAi8A57n5peiKJSH2bMHcCxz12HB0278ATJz5Bvz37YVZzZLiISN0SKijcfZWZ7QWsSlMe\nEYnAYR0O4/ajb+fMfc+kRdMWUccRkSwUplPmwwQdMEWkgdik+Sacv9/5KiZEJLQwnTKbA4PN7Eig\nFFg71bYBHvZWiJn1BoYAecC2wO/c/T81njMCOIdg8qzpBPNhzA5zPREREUmdMC0UewNlwAqgM7Bv\njS2sTYCZwEWx7736QTMbGjs2KJahAnjJzFoncU2RRqFkfgnvfPVO1DFEpAELM8rjkDTkwN0nAhOB\nX3UGs2DHJcBf3f3F2L7zgM+BUwmmAReRGj5a9BGXvXwZT815inPyzuGevvpREZH0CNNCAYCZ7W1m\nR5vZJrHv09klvAOwDfDy2h3uvgqYyi+zc4pITOWPlfzxuT/S6Y5OzPhiBg8d/xB3HXNX1LFEpAFL\nuIXCzLYB/gN0I7gt0RH4BLjdzFa5+8WpjQhAu9jXr2rs/xrITcP1RLLST6t+4pZpt/D3//2dJtaE\nkYeN5I/d/sjGzTeOOpqINHBhOmWOBr4h6Dj5cbX9TwB3A+koKOri6zs4ePBg2rRps86+goICClI9\ntaBIGlVWVlJYWMSrr84GmtK//xoOPrgTRUWF5OTk/Py8lWtWsvedezN/yXwu3P9Cruh9BW03aRtd\ncBHJeMXFxRSvnY43ZsmSJaFey9zX+5n86xPMlgAHuPtsM/sB2MfdPzGzHYFyd0963JmZVQHHr13R\n1Mx2IShe9qo+qsPMngK+d/dBNc7PA0pLS0vJS8eUgiL1ZOHChfTseQrl5dcD3QkGU1UBM8jNHU5J\nybh1ioqxs8ZywA4HkLulGu5EJJyysjLy8/MB8t29LN7zwvShaAIsr2X/FsDSEK8XjwqC2x191u6I\nzdp5EMHKpiIN0tChN8SKiR4ExQQEP4I9KC8fSWFh0TrPH9BlgIoJEYlEmIJiKvD7Wvb/BXglbBAz\na2VmXWPrhADsEvt+Rw+aUW4BrjSzI8wsF7iLYMbOR8NeUyTTzZgxm6BlojbdY8dFRKIXpg/FX4BX\nzWx/oAVwrZntTTAK48AksuwPTI49duDm2OMxwJnuXmRmGwMPErSGTAOOdPcfk7imSEZbvbopP7dM\ntPwOOrwCc06IHW0SOy4iEr0w81DMNrMuwAVAU4IP9/HA7e6+IGwQd5/CBlpM3P0a4Jqw1xDJNs2a\nrYGmy2H/O+Hga8GqoOIwWL45UBUcFxHJAGFaKIgVDlelOIuIVFPlVbQ9tAkckQttvoKys2HKiFgx\nATCdbt06RRlRRORnoQoKM2sLHABszi89xQBw94dSkEukUXv101cZ8tIQ3sx5k03mb8VPj4yFb04m\naMSrAqaTm3s5RUXjIk4qIhIIM7HVSQT9GppT+6gOFRQNTHFxsAEsXw7z5kH79tCyZbCvoCDYJDWu\nffVarppyFftvtz9TzphCp1adKFxTxKuvjqWioikdOqydh2LdIaMiIlEKMw/FZ8A44Ep3r234aOQ0\nD0X6lJVBfj6UloLe2vR49+t3mV05mxM7n0gT+6Vbkd57EakPYeehCHPLYyvg1kwtJkSy3d7b7M3e\n2+wddQwRkYSEmYfiRSA/1UFEREQke4VpoZgA/NPMOgPvE/QQ+9na6bJF5NfcnQlzJ3Dwzgez2Uab\nRR1HRCRlwhQU98a+XlvH8dBLoos0ZNM/n86Ql4Yw9bOp3Nv3Xs7OOzvqSCIiKZPwh7+7N1nflo6Q\nItms/NtyTn7yZHrc14PFyxfz/O+f56x9z4o6lohISoWah2ItM9sEWOaJDhURaQS++ekbrnvtOu54\n8w62brU19x97P6fvczpNm2i6bBFpeMLMQ9EMuA44h2Biq47AJ2Z2FfCVu9+T2oiSCSorKyksLOLV\nV2cDTenff+1cCIWaC6EWH37zId3/1Z0qr2LEISO4pMclbNJ8k6hjiYikTZgWipHA74ALgQeq7X8P\nGAaooGhgFi5cSM+ep8SW0S4CjIqKKioqZjB16smUlGiCpZp222o3hvcazqCug8hppfdGRBq+MH0e\nTgfOdvdxQPWViWYCe6UklWSUoUNviBUTPfhlpvUmQA/Ky0dSWFgUXbgMZWYUHlioYkJEGo0wLRSb\nA5/Usr8pwbLj0sDMmDGboGWiNt2ZMeO6+ozTqNSc9ny33WDYME17LiKZJ0xBMRvoBRTX2N+PoJVC\nGpjVq5tSYw24aprEjjcu85fMZ/738+m5Y8+0XkcFg4hkizAFxQhgjJm1I2iVOMbMOgLnAn1TmE0y\nRLNmawgan2orKqpixxuHJcuX8Pf//Z1bpt9Cl226MO2saZjVVWyJiDQeYeaheBY4laBjpgN/B/YF\n+rr7i6mNJ5mgW7dOwPQ6jk6PHW/YVq5Zya3TbyX31lz+Of2f/OWAv/DSaS+pmBARiQk1D4W7vwC8\nkOIskqGKigqZOvVkystHAt0J6tAqYDq5uZdTVDQu2oBp5O48OftJLnv5MioWVzCo6yD+euhf2W7T\n7aKOJiKSUZKa2Eoah5ycHEpKxsXmobiOioqmdOiwdh6Khj1k9PhxxzP+w/Ec3fFonjnlGfbaWgOZ\nRERqo4JC4pKTk8MDD9xAWRnk58OTT0JeXtSp0u/0LqdzcfeLOazDYVFHERHJaCooRNajX6d+UUcQ\nEckKWsxLREREkpZQQWFmzc3sEzPbPV2BROrL6qrVPPvhs1HHEBFpEBIqKNx9FdASWJ2eOCLp5+5M\nmDuBfe7ah2MfO5ZZX8+KOpKISNYLc8vjNqDQNABfstBbX77FYQ8dRt/ivmzdamvePOdNumzTJepY\nIiJZL0ynzG5AH+BoM3sHWFXtmLv7CSlJJpJCFd9VcPnkyyl+r5hOOZ2YUDCBozserYmpRERSJExB\nsQR4uo5jWhxMMs7Tc56m4KkCttp4K/7V91+c0fUMmjXRACcRkVRK+Lequw9MQw7JYNm+4uWBOx7I\nVb2v4pIel9CqRauo44iINEih/kwzsxbAUcCOwFh3/97Mtge+d/cfUhmw2jVHAFfV2P2Vu2sO5DTL\n9IJhQ7ZpvQ2X97486hgiIg1awgWFme0GvAhsAbQCJgLfA38CtgLOTmXAGt4DDq/2feNZ5lJERCSD\nhRnlcSvwMtAWWFZt/39Y98M+Hda4+8Jq26I0X0+ywHsL32Pe4nlRxxARadTCFBS9gL/F5qSo7jMg\n3bcfOprZAjP7ysz+bWZ7pvl6ksG++P4Lzh5/NvvctQ83ldwUdRwRkUYtTB+KFUDTWvZvByxOLs56\nvQEUAHOBrYHLgalmtre7L0jjdSXDfL/ie4peL+Lmkptp1aIVtxx1C+ftd17UsUREGrUwBcVLwB+B\nP6zdYWYtgWuA51KU61fc/cVq335oZscC5cCZwMjazhk8eDBt2rRZZ19BQQEF2dzDsBFbtWYV95Te\nwzWvXsMPK3/g0h6XUnhgIW1attnwySIi8ivFxcUUrx3GF7NkyZJQr2XuiU0dERvN8QqwHNiToOVg\nT+A7oLe7fx0qSQhm9l9gvrufX2N/HlBaWlpKXmNYY7sRWLpyKfn35PPRoo84o+sZXHvoteyw2Q5R\nxxIRaXDKysrIz88HyHf3snjPCzMPxRdm1hU4Bcgn6IfxMPCIuy9b78kpZGbNgM5ASX1dU6LTukVr\nztr3LH6z6280VbaISAYKNQ+Fu/8E3B/b6oWZjQT+S9D5Mwe4AtgceLC+Mki0Cg8sjDqCiIjUIa6C\nItZfYaK7r4w9rpO7j09Jsl/rCDxFMFx1KfA/4GB3n5+m64mIiEic4m2heAZoByyMPV6fMENRN8jd\nT0rH60pm+GnVT5QtKOOgnQ6KOoqIiIQQ14e/uzdx94XVHte5pTeuNDRrqtZw/8z76XhbR45/7HiW\nraq3bjgiIpJCCRUAZtbczF4xs13TFUgaB3fn+Y+ep+vdXTlr/Fn02qkXM86ZwcbNN446moiIhJBQ\np0x3X2VmewE1Z8kUiVvZgjIKXyrk5YqX6d2+N9PPnk637btFHUtERJIQ5hbFwwSTSYkk7Jop15B/\nTz5f/vAl408Zz5QzpqiYEBFpAMIMG20ODDazI4FSYGVsvwHu7pemKpw0PL3b9+buY+7mzH3PpFmT\nUKOWRUQkA4X5jb43sHbmrM7V9huQ2LSb0ugc2uFQDu1waNQxREQkxRIqKMysKTACeMfdv0tLIhER\nEck6ibZQVAEvEEwypYJCfuX1z16n2/bdaN60eb1et7g42ACWL4d586B9e2jZMthXUBBsIiKSHomO\n8nAzexfYkWAKbBEAZlfOZuikoUyYO4FHT3iUgr3r99O7esFQVgb5+UGBobXhRETqR5hRHsOBW8zs\nKDNra2abVd9SHVAy24IfFnDus+ey95178/7C93ms32OcstcpUccSEZF6FqZT5sTY1+drOeZA0/Bx\nJFv8sOIHbnzjRm4suZGWzVpy05E3ccF+F7BRs42ijiYiIhEIU1AclvIUklXe+eodjhp7FIuXL+bi\n7hdzWa/L2Lzl5lHHEhGRCCVcULj7lDTkkCyyR9s9KNirgMEHDGanNjtFHUdERDJA6JmFzGwrghVI\n17nF4e6zkg0lmW2jZhsx6jejoo4hIiIZJOGCwsy2BYqB3rUcVh8KERGRRijMKI/bY+flAz8BhwMn\nAx8Ax6UumkTlm5++4YNvPog6hoiIZJEwBUUfYIi7zySY6Oozd38CGAwMS2U4qV/LVi3jH//7B7m3\n5vKH5/4QdRwREckiYQqKFsDnscc/AW1jjz8kaLWQLLOmag0PvfMQu4/enSteuYIz9jmD4n7FUcdK\nWGVlJYMGDaF//98Cx9K//28ZNGgIlZWVUUcTEWnwwnTK/ADYHfgCeBs4x8wqgAuARSnMJvXgpfKX\nGPLSEN75+h36d+rP3/r8jV233DXqWAlbuHAhPXueQnn59UARYFRUVFFRMYOpU0+mpGQcOTk5UccU\nEWmwwrRQ3AJsH3t8FdAPWABcClyZolySZu7O78b9jiPHHknrFq0pOauEJ058IiuLCYChQ2+IFRM9\nCBa+heCfdw/Ky0dSWFgUXTgRkUYgzDwUD1Z7PMPMdgL2Aj519y9TGU7Sx8zo06EPp3c5neP3OB4z\n2/BJGWzGjNkELRO16c6MGdfVZxwRkUYn9DwUAGbWHFjm7m+kKI/Uoz90azgdL1evbsovLRM1NYkd\nFxGRdAlzywMz+5OZzQVWACvMbK6ZXZLaaCLxa9ZsDcE0KLWpih0XEZF0SbigMLNrgesIJrf6bWwr\nBq4xs5GpjSdhuTszvpgRdYx6061bJ2B6HUenx46LiEi6hGmhuAA43d2vdvfnY9vVwBnA+amNJ2FM\nnTeVA+47gB7/6kH5t+VRx6kXRUWF5OYOB0oIpkch9rWE3NzLKSoqjC6ciEgjEKagaArMrGX/22ja\n7Uh98M0HHP/Y8fQe05tVVauYdPokcrfMjTpWvcjJyaGkZBwDBz5Nhw59gWPp0KEvAwc+rSGjIiL1\nIEynzEcIWiIuq7H/HODRpBNJwr5e+jUjpozg3rJ72WGzHXjkhEc4Za9TaGKhushkrZycHB544AbK\nyiA/H558EvLyok4lItI4xFVQmNkofunx5sBFZvYbYFpsXw8gF3iwltNTyswuBIYQrHT6PnCJu/8v\n3dfNVE+8/wRnjj+T5k2aU3REERftfxEbNdso6lgiItLIxNtCsS/rdqEvi33dI/Z1SWzfXinKVSsz\nOxm4iaC/xjTgPOB5M+vk7vPTee1MtdfWe3Fe/nlc3utytth4i6jjiIhIIxVXQeHuh6Q5R7wuBe5w\n98dj319uZkcTdBQdHl2s6OyZsyc3Hnlj1DFERKSRS2piq/pkZi2APOCaGodeBnrWf6L0KC4ONoDl\ny2HePGjfHlq2DPYVFASbiIhIJsmagoJgVdOmwFc19n9N0J+iQaheMJSVQX6fCu5+cHMO6aHbGSIi\nkrkawjCAuqZHzGrfLvuWm9+/FP6wB2M/uTnqOCIiIuuVTS0U3wBr+HVrxLYEq53+yuDBg2nTps06\n+woKCijI4HsGy1cv57bpt3H9/65n5arV8NqVDOo7OOpYIiLSABUXF1O89j57zJIlS0K9VtYUFO6+\n0sxKgT7Ac9UOHQo8X9s5o0aNIi9LJiKo8ioeffdRLp98OV98/wXn5Z/H8VtexZFXbsPGWfN/SURE\nskltf2SXlZWRn5+f8Gtl20fVzcAYM5sGvAmcDewK3BVpqiQt+mkRRzx8BDO/msnv9vgdLw54kd3b\n7k5Z2YbPFRERyQRZVVC4++NmthVQRHCr413g6Gyfg2LLjbfkwB0P5Nb/u5WDdjoo6jhZqebomN12\ng2HDNDpGRKS+ZFVBAeDudwJ3Rp0jlcyM246+LeoYWU0Fg4hItBrCKA8RERGJmAqKerBqzSrmVM6J\nOoaIiEjaqKBII3fnqdlP0fmOzhw19ihWV62OOpKIiEhaqKBIkzfmv8GB9x9I/yf6k7tlLhNOnUCz\nJvF1WamsrGTQoCH07/9b4Fj69/8tgwYNobKyMr2hRUREQsq6TpmZbu6iuVz28mU8Pedp9m23Ly+d\n9hKH73J43OcvXLiQnj1Pobz8eoLBLEZFRRUVFTOYOvVkSkrGkZOTk7b8IiIiYaiFIoX++upf6XxH\nZ9768i0e/t3DvHXuWwkVEwBDh94QKyZ6ABbb2wToQXn5SAoLi1KcWkREJHkqKFJo1y135frDrufD\nP3zIgC4DaGKJv70zZswGutdxtHvsuIiISGbRLY8UOnXvU5N+jdWrm/JLy0RNTWLHRUREMotaKDJM\ns2ZrqHsB1arYcRERkcyigiIBcyrn4J7e1dK7desETK/j6PTYcRERkcyigiIO8xbPY8DTA+h0Ryde\nKH8hrdcqKiokN3c4UAJUxfZWASXk5l5OUVFhWq8vIiIShgqK9fhu2XcMeXEIu43ejUmfTOLuY+5O\neNRGonJycigpGcfAgU/ToUNf4Fg6dOjLwIFPa8ioiIhkLHXKrMWK1Su4/c3bue6161i5ZiXDDxrO\nn3v+mdYtWtfL9XNycnjggRsoK4P8fHjyScjLq5dLi4iIhKKCoobSL0vp/0R/5i+Zz9l5ZzPikBG0\na90u6lgiIiIZTQVFDR226MABOxzAc6c+x545e0YdR0REJCuooKhhy4235NF+j0YdQ0REJKuoU6aI\niIgkrdEVFD+s+IEFPyyIOoaIiEiD0mgKilVrVnHXW3fR8baO/Gnin6KOIyIi0qA0+D4U7s74D8cz\ndNJQ5i6ay2n7nMa1h14bdSwREZEGpUEXFO9+/S6XjLmEqZ9N5YhdjuCx/o/RtV3XqGOJiIg0OA26\noBj4zED27ro3E38/kaN2PSrqOHEpLg42gOXLYbfdYNgwaNky2FdQEGwiIiKZpEEXFFcfcjVXnnwl\nTZtkz5LfKhhERCQbNehOmcfufmxWFRMiIiLZqkEXFCIiIlI/VFCIiIhI0lRQiIiISNJUUIiIiEjS\nsqagMLNPzayqxnZ91LkamuK1Y1YlbnrPwtH7lji9Z+HofasfWVNQAA5cCbSrto2MNFEDpB+8xOk9\nC0fvW+L0noWj961+ZNs8FEvdfWHUIURERGRd2dRCATDMzL41s7lmNtLMWkQdSERERLKrheJGoBT4\nDtg/9v0ugOaVFBERiVikBYWZjQCu2sDT9nP3Mne/vdq+D83sW2CCmf3Z3b+scU5LgDlz5qQubCOx\nZMkSysrKoo6RVfSehaP3LXF6z8LR+5aYap+dLRM5z9w99WnivbjZVsBWG3jaPHdfUcu5WwNfAT3d\nfVqNY6cCj6QsqIiISOPze3d/NN4nR9pC4e6LgEUhT98n9vXzWo69APwe+BRYHvL1RUREGqOWwM4E\nn6Vxi7SFIl5m1h3IB6YA38ce3waUuvvvIowmIiIiZE9BsS9wN7AHsDHwJTAOuNrdl0WZTURERLKk\noBAREZHMlm3zUIiIiEgGUkEhIiIiSWsUBYWZ/dbMppvZT2b2nZk9E3WmbGFmG5nZ27HF2LpEnSdT\nmVkHM3vYzD4zs5VmNt/M/qHZXH/NzC40swozW2Zmb5nZQVFnymRmdpWZlcberyVm9pyZ7Rl1rmxi\nZsNiv8NGRZ0l05nZ9mY21sy+MbPlZjb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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#get results for 4x4 supercell with def Equil\n", "\n", "#plotting\n", "plt.errorbar(largestSuperCell_DFT_ki.barrierEnergy()-smallestSuperCell_DFT_conv.barrierEnergy(),largestSuperCell_DMC_ki.barrierEnergy_defEquil(), yerr=largestSuperCell_DMC_ki.barrierError_defEquil(), fmt='o')\n", "plt.xlabel(\"barrier energy DFT(k) - DFT(k point converged)\")\n", "plt.ylabel(\"barrier energy DMC(k)[kcal/mol]\");\n", "\n", "#linear regression\n", "[popt,pcov]=curve_fit(func,largestSuperCell_DFT_ki.barrierEnergy()-smallestSuperCell_DFT_conv.barrierEnergy(),largestSuperCell_DMC_ki.barrierEnergy_defEquil(), sigma=largestSuperCell_DMC_ki.barrierError_defEquil())\n", "[a, erra]=[popt[0], np.sqrt(np.diag(pcov))[0]]\n", "[b, errb]=[popt[1], np.sqrt(np.diag(pcov))[1]]\n", "ax=plt.gca()\n", "xmin, xmax = ax.get_xlim()\n", "plt.plot([xmin, xmax], [func(xmin,a,b), func(xmax,a,b)], '--');\n", "plt.savefig(\"kpoints4x4.svg\")\n", "print 'a=',a,'+/-',erra\n", "print 'b=',b,'+/-',errb\n", "print\n", "\n", "#means and corrections over k-points for DFT, DMC, smallest supercell\n", "#correction for DMC scaled by factor a from linear regression\n", "dftNoCorr=sum(largestSuperCell_DFT_ki.barrierEnergy()*largestSuperCell_DFT_ki.weight())/sum(largestSuperCell_DFT_ki.weight())\n", "dmcNoCorr=sum(largestSuperCell_DMC_ki.barrierEnergy_defEquil()*largestSuperCell_DMC_ki.weight())/sum(largestSuperCell_DMC_ki.weight())\n", "corrDft=smallestSuperCell_DFT_conv.barrierEnergy()-dftNoCorr#mean(largestSuperCell_DFT_ki.barrierEnergy())\n", "corrDmc=corrDft*a\n", "errCorrDmc=corrDmc*erra/a\n", "statErrDmc=np.sqrt(sum((largestSuperCell_DMC_ki.barrierError_defEquil()*largestSuperCell_DMC_ki.weight())**2))/sum(largestSuperCell_DMC_ki.weight())\n", "print 'method\\t av. over k \\t corr. from DFT \\t sum \\t uncert. from a \\t stat. uncert.' \n", "print 'DFT\\t', dftNoCorr, '\\t', corrDft, '\\t', dftNoCorr+corrDft, '\\t', 0.00000, '\\t\\t',0.00000 \n", "print 'DMC\\t', dmcNoCorr, '\\t', corrDmc, '\\t', dmcNoCorr+corrDmc, '\\t', errCorrDmc, '\\t',statErrDmc \n", "dmc4x4=dmcNoCorr+corrDmc\n", "errDmc4x4=sqrt(errCorrDmc**2+statErrDmc**2)\n", "print errDmc4x4\n" ] }, { "cell_type": "code", "execution_count": 69, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "dmcExt, errDmcExt 13.0383599206 0.988805596035\n" ] } ], "source": [ "#finite size extrap\n", "xVal2x2=(1./4.)**(-5./4.)\n", "xVal4x4=(1)**(-5./4.)\n", "xx=[xVal2x2, xVal4x4]\n", "yy=[dmc2x2[0], dmc4x4[0]]\n", "sigma=[errDmc2x2[0], errDmc4x4[0]]\n", "#linear regression\n", "[popt,pcov]=curve_fit(func,xx,yy, sigma=sigma, absolute_sigma=True)\n", "[a, erra]=[popt[0], np.sqrt(np.diag(pcov))[0]]\n", "[b, errb]=[popt[1], np.sqrt(np.diag(pcov))[1]]\n", "print \"dmcExt, errDmcExt\", b, errb\n", "#finite size extrap (old)\n", "dmcExt=dmc4x4-(dmc2x2-dmc4x4)/(xVal2x2-xVal4x4)*xVal4x4\n", "dmcExtMin=(dmc4x4-errDmc4x4)-(dmc2x2+errDmc2x2-(dmc4x4-errDmc4x4))/(xVal2x2-xVal4x4)*xVal4x4\n", "dmcExtMax=(dmc4x4+errDmc4x4)-(dmc2x2-errDmc2x2-(dmc4x4+errDmc4x4))/(xVal2x2-xVal4x4)*xVal4x4\n", "#print 'dmc2x2, dmc4x4:', dmc2x2, dmc4x4\n", "#print 'errDmc2x2, errDmc4x4:',errDmc2x2, errDmc4x4\n", "#print 'corr:', -(dmc2x2-dmc4x4)/(xVal2x2-xVal4x4)*xVal4x4\n", "#print 'dmcExt:', dmcExt\n", "#print 'dmcExtMin:', dmcExtMin, dmcExt-dmcExtMin\n", "#print 'dmcExtMax:', dmcExtMax, dmcExtMax-dmcExt" ] }, { "cell_type": "code", "execution_count": 70, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "method\t av. over k \t corr. from DFT \t sum \t uncert. from a \t stat. uncert.\n", "DFT\t9.70898421151 \t[ 0.64727121] \t[ 10.35625542] \t0.0 \t\t0.0\n", "DMC\t10.9695422317 \t[ 0.19841387] \t[ 11.1679561] \t[ 0.14735607] \t0.662009250509\n" ] } ], "source": [ "#means and corrections over k-points for DFT, DMC, smallest supercell without weights\n", "#correction for DMC scaled by factor a from linear regression\n", "dftNoCorr=sum(largestSuperCell_DFT_ki.barrierEnergy())/len(largestSuperCell_DFT_ki.barrierEnergy())\n", "dmcNoCorr=sum(largestSuperCell_DMC_ki.barrierEnergy())/len(largestSuperCell_DMC_ki.barrierEnergy())\n", "corrDft=smallestSuperCell_DFT_conv.barrierEnergy()-dftNoCorr#mean(largestSuperCell_DFT_ki.barrierEnergy())\n", "corrDmc=corrDft*a\n", "errCorrDmc=corrDmc*erra/a\n", "statErrDmc=np.sqrt(sum((largestSuperCell_DMC_ki.barrierError())**2))/len(largestSuperCell_DMC_ki.barrierEnergy())\n", "print 'method\\t av. over k \\t corr. from DFT \\t sum \\t uncert. from a \\t stat. uncert.' \n", "print 'DFT\\t', dftNoCorr, '\\t', corrDft, '\\t', dftNoCorr+corrDft, '\\t', 0.00000, '\\t\\t',0.00000 \n", "print 'DMC\\t', dmcNoCorr, '\\t', corrDmc, '\\t', dmcNoCorr+corrDmc, '\\t', errCorrDmc, '\\t',statErrDmc " ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 2", "language": "python", "name": "python2" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 2 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython2", "version": "2.7.8" } }, "nbformat": 4, "nbformat_minor": 0 }