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How to use analysis2 method in autotest
Best Python code snippet using autotest_python
makedatafile_t2kcc0pi.py
Source:makedatafile_t2kcc0pi.py 
1from ROOT import *2from array import *3def GetMiddle(mystr):4 lims = mystr.strip().split(" - ")5 val = (float(lims[0]) + float(lims[1]))/2.06 return val7def GetLowEdge(mystr):8 lims = mystr.strip().split(" - ")9 val = (float(lims[0]) + 0.00001)10 11 return val12def GetHighEdge(mystr):13 14 lims = mystr.strip().split(" - ")15 val = (float(lims[1]) - 0.00001)16 17 return val18 19def GetIndex(mystr):20 lims = mystr.split("-")21 return int(lims[0]), int(lims[1])22outfile = TFile("T2K_CC0PI_2DPmuCosmu_Data.root","RECREATE")23# ANALYSIS I24#______________________________25xedge = [0.0, 0.3, 0.4, 0.5, 0.65, 0.8, 0.95, 1.1, 1.25, 1.5, 2.0, 3.0, 5.0, 30.0]26yedge = [-1.0, 0.0, 0.6, 0.7, 0.8, 0.85, 0.9, 0.94, 0.98, 1.0]27datahist = TH2D("analysis1_data","analysis1_data",28 len(xedge)-1, array('f',xedge),29 len(yedge)-1, array('f',yedge))30 31maphist = datahist.Clone("analysis1_map")32maphist.SetTitle("analysis1_map")33 34counthist = datahist.Clone("analysis1_entrycount")35datapoly = TH2Poly("datapoly","datapoly", 0.0,30.0, -1.0, 1.0)36hist = None37binedges = []38histedgeslist = []39xsecvals = []40histxseclist = []41binlimits = [3,8,15,22,30,39,47,58,67]42with open("cross-section_analysisI.txt") as f:43 count = 044 for line in f:45 count += 146 47 if (count < 4): continue48 data = line.strip().split("|")49 if (len(data) < 1): continue50 ibin = int( data[0] ) + 151 52 xval = round(float(GetLowEdge( data[2] )),4)53 yval = round(float(GetLowEdge( data[1] )),4)54 xhig = round(float(GetHighEdge( data[2] )),4)55 yhig = round(float(GetHighEdge( data[1] )),4)56 57 xsec = float( data[3] ) * 1E-3858 datapoly.AddBin( xval, yval, xhig, yhig )59 datapoly.SetBinContent( datapoly.GetNumberOfBins(), xsec)60 binedges.append( xval )61 xsecvals.append( xsec )62 if ibin in binlimits: 63 binedges.append( xhig )64 histedgeslist.append(binedges)65 histxseclist.append(xsecvals)66 binedges = []67 xsecvals = []68 datahist.Fill(xval, yval, xsec)69 counthist.Fill(xval, yval, 1.0)70 for i in range(maphist.GetNbinsX()):71 for j in range(maphist.GetNbinsY()):72 xcent = maphist.GetXaxis().GetBinCenter(i+1)73 ycent = maphist.GetYaxis().GetBinCenter(j+1)74 if (xcent > xval and xcent < xhig and75 ycent > yval and ycent < yhig):76 maphist.SetBinContent(i+1,j+1, ibin)77# Get Covariances (keep in 1E-38 cm^2) \78nbins = 6779statcov = TH2D("analysis1_statcov","analysis1_statcov", nbins, 0.0, float(nbins), nbins, 0.0, float(nbins));80systcov = TH2D("analysis1_systcov","analysis1_systcov", nbins, 0.0, float(nbins), nbins, 0.0, float(nbins));81normcov = TH2D("analysis1_normcov","analysis1_normcov", nbins, 0.0, float(nbins), nbins, 0.0, float(nbins));82totcov = TH2D("analysis1_totcov","analysis1_totcov", nbins, 0.0, float(nbins), nbins, 0.0, float(nbins));83with open("covariance_statisticUncertainty_analysisI.txt") as f:84 count = 085 for line in f:86 count += 187 if (count < 4): continue88 data = line.strip().split("|")89 if (len(data) < 1): continue90 xi, yi = GetIndex(data[0])91 cov = float(data[1])92 statcov.SetBinContent(xi + 1, yi + 1, cov)93with open("covariance_shapeSystematics_analysisI.txt") as f:94 count = 095 for line in f:96 count += 197 if (count < 4): continue98 data = line.strip().split("|")99 if (len(data) < 1): continue100 xi, yi = GetIndex(data[0])101 cov = float(data[1])102 systcov.SetBinContent(xi + 1, yi + 1, cov)103with open("covariance_fluxNormalizationSystematics_analysisI.txt") as f:104 count = 0105 for line in f:106 count += 1107 if (count < 4): continue108 data = line.strip().split("|")109 if (len(data) < 1): continue110 xi, yi = GetIndex(data[0])111 cov = float(data[1])112 normcov.SetBinContent(xi + 1, yi + 1, cov)113totcov.Add(systcov)114totcov.Add(statcov)115totcov.Add(normcov)116data1D = TH1D("datahist","datahist", datapoly.GetNumberOfBins(), 0.0, float(datapoly.GetNumberOfBins()));117for i in range(datapoly.GetNumberOfBins()):118 data1D.SetBinContent(i+1, datapoly.GetBinContent(i+1));119 data1D.SetBinError(i+1, sqrt(totcov.GetBinContent(i+1,i+1))*1E-38)120outfile.cd()121for i, obj in enumerate(histedgeslist):122 print obj123 hist = TH1D("dataslice_" + str(i), "dataslice_" + str(i), len(obj)-1, array('f',obj))124 for j in range(hist.GetNbinsX()):125 hist.SetBinContent(j+1, histxseclist[i][j])126 hist.GetXaxis().SetRangeUser(obj[0], obj[len(obj)-2])127 hist.Draw("HIST")128 gPad.Update()129 hist.SetNameTitle("dataslice_" + str(i),"dataslice_" + str(i))130 hist.Write()131outfile.cd()132datahist.Write()133counthist.Write()134maphist.Write()135datapoly.Write()136data1D.Write()137statcov.Write()138systcov.Write()139totcov.Write()140normcov.Write()141# ANALYSIS II142#______________________________143xedge = [0.2, 0.35, 0.5, 0.65, 0.8, 0.95, 1.1, 1.25, 1.5, 2.0, 3.0, 5.0, 30.0]144yedge = [0.6, 0.7, 0.8, 0.85, 0.9, 0.925, 0.95, 0.975, 1.0]145datahist = TH2D("analysis2_data","analysis2_data",146 len(xedge)-1, array('f',xedge),147 len(yedge)-1, array('f',yedge))148maphist = datahist.Clone("analysis2_map")149maphist.SetTitle("analysis2_map")150counthist = datahist.Clone("analysis2_entrycount")151# Get Data Entries152entries = []153count = 0154with open("rps_crossSection_analysis2.txt") as f:155 for line in f:156 count += 1157 if (count < 4): continue158 data = line.strip().split("|")159 if (len(data) < 1): continue160 ibin = int( data[0] ) + 1161 xval = GetMiddle( data[2] )162 yval = GetMiddle( data[1] )163 xsec = float( data[3] ) * 1E-38164 datahist.Fill(xval, yval, xsec)165 maphist.Fill(xval, yval, ibin)166 167 counthist.Fill(xval, yval, 1.0)168 # print ibin, "Map Value"169 170# Get N Bins171nbins = int(maphist.GetMaximum())172print "NBins I = ", nbins173# Get Covariances (keep in 1E-38 cm^2)174statcov = TH2D("analysis2_statcov","analysis2_statcov", nbins, 0.0, float(nbins), nbins, 0.0, float(nbins));175systcov = TH2D("analysis2_systcov","analysis2_systcov", nbins, 0.0, float(nbins), nbins, 0.0, float(nbins));176normcov = TH2D("analysis2_normcov","analysis2_normcov", nbins, 0.0, float(nbins), nbins, 0.0, float(nbins));177totcov = TH2D("analysis2_totcov","analysis2_totcov", nbins, 0.0, float(nbins), nbins, 0.0, float(nbins));178with open("rps_statsCov_analysis2.txt") as f:179 count = 0180 for line in f:181 count += 1182 183 if (count < 4): continue184 data = line.strip().split("|")185 if (len(data) < 1): continue186 xi, yi = GetIndex(data[0])187 cov = float(data[1])188 statcov.SetBinContent(xi + 1, yi + 1, cov)189with open("rps_systCov_analysis2.txt") as f:190 count = 0191 for line in f:192 count += 1193 194 if (count < 4): continue195 data = line.strip().split("|")196 if (len(data) < 1): continue197 198 xi, yi = GetIndex(data[0])199 cov = float(data[1])200 201 systcov.SetBinContent(xi + 1, yi + 1, cov)202with open("rps_fluxNormCov_analysis2.txt") as f:203 count = 0204 for line in f:205 count += 1206 207 if (count < 4): continue208 data = line.strip().split("|")209 if (len(data) < 1): continue210 211 xi, yi = GetIndex(data[0])212 cov = float(data[1])213 214 normcov.SetBinContent(xi + 1, yi + 1, cov)215 216totcov.Add(systcov)217totcov.Add(statcov)218totcov.Add(normcov)219outfile.cd()220datahist.Write()221maphist.Write()222counthist.Write()223statcov.Write()224systcov.Write()225totcov.Write() 226normcov.Write() ...
finalproject.py
Source:finalproject.py
1import pandas as pd2import numpy as np3import os4# df = pd.read_csv('USvideos_new.csv', engine='python')5# print(df.head(5))6# from textblob import TextBlob7# pola = []8# polas = []9# subj = []10# subjs = []11# for index, row in df.iterrows():12# analysis = TextBlob(row['title'])13# pola.append(analysis.sentiment[0])14# subj.append(analysis.sentiment[1])15# if type(row['description']) == type('str'):16# analysis2 = TextBlob(row['description'])17# polas.append(analysis2.sentiment[0])18# subjs.append(analysis2.sentiment[1])19# else:20# polas.append(0)21# subjs.append(0)22# df['polarity'] = pola23# df['subjectivity'] = subj24# df['polarity_description'] = polas25# df['subjectivity_description'] = subjs26# print(df.head(5))27# df.to_csv('out.csv')28# df = pd.read_csv('UKvideos_new.csv', engine='python')29# print(df.head(5))30# from textblob import TextBlob31# pola = []32# polas = []33# subj = []34# subjs = []35# for index, row in df.iterrows():36# analysis = TextBlob(row['title'])37# pola.append(analysis.sentiment[0])38# subj.append(analysis.sentiment[1])39# if type(row['description']) == type('str'):40# analysis2 = TextBlob(row['description'])41# polas.append(analysis2.sentiment[0])42# subjs.append(analysis2.sentiment[1])43# else:44# polas.append(0)45# subjs.append(0)46# df['polarity'] = pola47# df['subjectivity'] = subj48# df['polarity_description'] = polas49# df['subjectivity_description'] = subjs50# print(df.head(5))51# df.to_csv('outuk.csv')52df = pd.read_csv('CAvideos_new.csv', engine='python')53print(df.head(5))54from textblob import TextBlob55pola = []56polas = []57subj = []58subjs = []59for index, row in df.iterrows():60 analysis = TextBlob(row['title'])61 pola.append(analysis.sentiment[0])62 subj.append(analysis.sentiment[1])63 if type(row['description']) == type('str'):64 analysis2 = TextBlob(row['description'])65 polas.append(analysis2.sentiment[0])66 subjs.append(analysis2.sentiment[1])67 else:68 polas.append(0)69 subjs.append(0)70df['polarity'] = pola71df['subjectivity'] = subj72df['polarity_description'] = polas73df['subjectivity_description'] = subjs74print(df.head(5))...
analysis2_csv_tweets_genre_yrmnth.py
Source:analysis2_csv_tweets_genre_yrmnth.py
1#Analysis-2 Starting here2import pandas as pd3import datetime4gen=pd.read_csv('genre.csv')5tweets=pd.read_csv('processed.csv')6mv=pd.read_csv('processed_movies.csv')7analysis2=tweets[['imdbID','created_year','created_month','retweet_count','favorite_count']]8analysis2['calc_ret_fav_count']=analysis2['retweet_count']+analysis2['favorite_count']9mv=mv[['Released','imdbID']]10mv=mv[~(mv['Released'].isnull())]11mv['Released_DateTime'] = mv['Released'].apply(lambda x: pd.to_datetime(str(x), format='%d %b %Y'))12mv['Released_Year']=mv['Released'].apply(lambda x: pd.to_datetime(str(x), format='%d %b %Y').year)13mv['Released_Year']=pd.to_numeric(mv['Released_Year']).round()14mv['Released_Month']=mv['Released'].apply(lambda x: pd.to_datetime(str(x), format='%d %b %Y').month)15mv['Released_Monthname']=mv['Released'].apply(lambda x: pd.to_datetime(str(x), format='%d %b %Y').strftime('%b'))16#mv['Released_Month']=mv['Released'].month17mv=mv.merge(gen, left_on=['imdbID'], right_on=['imdbID'], how='inner')18#print(mv.head(5))19analysis2=analysis2.merge(mv,left_on=['imdbID','created_year'], right_on=['imdbID','Released_Year'], how='inner')20analysis2=analysis2[['Genre','calc_ret_fav_count','created_year','Released_Monthname','Released_Month']]21analysis2=analysis2.groupby(['Genre','created_year','Released_Monthname','Released_Month'],as_index=False)['calc_ret_fav_count'].mean()...
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