block by michalskop 8155694

CZ presidential election 2013: instant runoff voting

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<h1>Voters transfers during Czech presidential elections 2013 using hypothetical instant runoff voting system</h1>

<p id="chart">

<p>The data is from research conducted among users of voting advice application <a href="//volebnikalkulacka.cz">Volební kalkulačka</a>. It is weighted so the 1st round of the real elections and the 2nd round of the real elections match the 1st and last round of the potentional <a href="//en.wikipedia.org/wiki/Instant-runoff_voting">instant-runoff voting (alternative vote) electoral system</a>.</p>
<p>The analysis flow: 
<ol><li>extract.py (from research.txt, not present because of the size) -> responses0</li>
<li>calc2.py -> groups18.csv</li>
<li>weights.R</li>
<li>calc3.py -> sankey.json</li>
</ol>
</p>

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calc2.py

# -*- coding: utf-8 -*-

# calculates 18 groups

import pickle
import csv

with open("responses0", 'rb') as f:
  responses = pickle.load(f)

out = {}
sums = {}
for jsonvar in responses:
  i = i + 1
  count = 0
  for key in jsonvar:
    try:
      if (jsonvar[key] == 1):
        count = count + 1
    except:
      nothing = 1
  for key in jsonvar:
    try:
      if (jsonvar[key] == 1):
        if jsonvar['zeman'] < jsonvar['schwarzenberg']:
          if key in sums:
            if 'zeman' in sums[key]:
              sums[key]['zeman'] = sums[key]['zeman'] + 1/count
            else:
              sums[key]['zeman'] = 1/count
          else:
            #print(jsonvar)
            sums[key] = {}
            sums[key]['zeman'] = 1/count
        else:
          if (jsonvar['schwarzenberg'] < jsonvar['zeman']):
            if key in sums:
              if 'schwarzenberg' in sums[key]:
                sums[key]['schwarzenberg'] = sums[key]['schwarzenberg'] + 1/count
              else:
                sums[key]['schwarzenberg'] = 1/count
            else:
              sums[key] = {}
              sums[key]['schwarzenberg'] = 1/count
    except:
      #del jsonvar[key]
      nothing = 1
print(sums)
writer = csv.writer(open('groups18.csv', 'wb'))
for key, value in sums.items():
  if 'zeman' not in value:
    value['zeman'] = 0
  if 'schwarzenberg' not in value:
    value['schwarzenberg'] = 0
  writer.writerow([key, value['zeman'], value['schwarzenberg']])
  print [key, value['zeman'], value['schwarzenberg']]

calc3.py

# -*- coding: utf-8 -*-

# calculates the transfers
# using weights from R (manually entered)

import json
import pickle

with open("responses0", 'rb') as f:
  responses = pickle.load(f)

out = {}
out["nodes"] = []
out["links"] = []
prevj = {}

i = 0
j = 0

people = {
  "zeman": {"name":"Zeman","color":"#FF0000"},
  "schwarzenberg":{"name":"Schwarzenberg","color":"#880088"},
  "fischer":{"name":"Fischer","color":"#0000FF"},
  "dienstbier":{"name":"Dienstbier","color":"#FFA500"},
  "franz":{"name":"Franz","color":"#000000"},
  "roithova":{"name":"Roithová","color":"#FFFF00"},
  "fischerova":{"name":"Fischerová","color":"#00AA00"},
  "sobotka":{"name":"Sobotka","color":"#000088"},
  "bobosikova":{"name":"Bobošíková","color":"#FFFF44"}
}

weights = {
  'zeman': {'zeman': 1.6800465}, 
  'fischer': {'zeman': 1.4850209, 'schwarzenberg': 1.6041692},
  'sobotka': {'zeman': 0.8815094, 'schwarzenberg': 0.5447683}, 
  'fischerova': { 'zeman': 0.7513741, 'schwarzenberg': 0.4237004}, 
  'schwarzenberg': {'schwarzenberg': 0.7202682}, 
  'dienstbier': {'zeman': 2.6144173, 'schwarzenberg': 0.7212448}, 
  'roithova': {'zeman': 1.4540868, 'schwarzenberg': 0.5347517}, 
  'bobosikova': {'zeman': 1.1143363, 'schwarzenberg': 1.1098767}, 
  'franz': {'zeman': 0.7372130, 'schwarzenberg': 0.3176280}}

wresponses = []
for jsonvar in responses:
  minkey = min(jsonvar, key=jsonvar.get)
  if jsonvar['zeman'] < jsonvar['schwarzenberg']:
    weight = weights[minkey]['zeman']
  else:
    if jsonvar['zeman'] > jsonvar['schwarzenberg']:
      weight = weights[minkey]['schwarzenberg']
    else:
      weight = 1
  wresponses.append({
    'values': jsonvar,
    'weight': weight
  })
  #print(wresponses)
  #raise Exception("diepy")

for n in range(1, 9):
  sums = {}
  for jsonvar in wresponses:
    i = i + 1
    count = 0
    for key in jsonvar['values']:
      try:
        if (jsonvar['values'][key] == 1):
          count = count + 1
      except:
        nothing = 1
    for key in jsonvar['values']:
      try:
        if (jsonvar['values'][key] == 1):
          if key in sums:
            sums[key] = sums[key] + jsonvar['weight']/count
          else:
            sums[key] = jsonvar['weight']/count
      except:
        #del jsonvar[key]
        nothing = 1
  print(sums)
  print sum(sums.itervalues())
  print len(responses)
  outkey = min(sums, key=sums.get)
  print(outkey)
  for item in sums:
    out["nodes"].append({"color":people[item]["color"],"name":people[item]["name"], "j": j})
    if (item == outkey):
      currentj = j
    if (n > 1):
      tmp = sums[item] - last[item]
      out["links"].append({"source":lastj,"target":j,"value":tmp})
      out["links"].append({"source":prevj[item],"target":j,"value":last[item]})
    prevj[item] = j
    j = j + 1  
     
  lastj = currentj
  
  for jsonvar in responses:
    for key in jsonvar:
      if (jsonvar[key] > jsonvar[outkey]):
        jsonvar[key] = jsonvar[key] - 1
    del jsonvar[outkey]
  last = sums
        #raise Exception("diepy")
        #raise Exception("diepy")
with open('sankey.json', 'w') as outfile:
  json.dump(out, outfile)  

extract.py

# -*- coding: utf-8 -*-

# extracts inputs
# only the correct ones

import json
import pickle
#fin = open('workfile.html', 'w')

responses = []
i = 0

with open("research.txt","r") as fin:
  for row in fin:
    ar = row.split("\t")
    #print(ar)
    jsonvar = json.loads(ar[3])
    newvar = {}
    try:
        if "input-sort-bobosikova" in jsonvar:
          newvar["bobosikova"] = int(jsonvar["input-sort-bobosikova"])
          if "input-sort-dienstbier" in jsonvar:
            newvar["dienstbier"] = int(jsonvar["input-sort-dienstbier"])
            if "input-sort-fischer" in jsonvar:
              newvar["fischer"] = int(jsonvar["input-sort-fischer"])
              if "input-sort-fischerova" in jsonvar:
                newvar["fischerova"] = int(jsonvar["input-sort-fischerova"])
                if "input-sort-franz" in jsonvar:
                  newvar["franz"] = int(jsonvar["input-sort-franz"])
                  if "input-sort-roithova" in jsonvar:
                    newvar["roithova"] = int(jsonvar["input-sort-roithova"])
                    if "input-sort-schwarzenberg" in jsonvar:
                      newvar["schwarzenberg"] = int(jsonvar["input-sort-schwarzenberg"])
                      if "input-sort-sobotka" in jsonvar:
                        newvar["sobotka"] = int(jsonvar["input-sort-sobotka"])
                        if "input-sort-zeman" in jsonvar:
                          newvar["zeman"] = int(jsonvar["input-sort-zeman"])
                          cc = 0
                          for n in range(1, 10):
                            if n in newvar.values():
                              cc = cc + 1
                          if (cc == 9):
                            responses.append(newvar)
                            i = i + 1
    except:
      nothing = 1
      
print (i)      
with open("responses0", 'wb') as f:
  pickle.dump(responses, f)
  
  
      #print(responses)
      #raise Exception('diePy')

groups18.csv

zeman,1673,0
fischer,553,658
sobotka,141,369
fischerova,201,528
schwarzenberg,0,3749
dienstbier,582,442
roithova,183,550
bobosikova,163,73
franz,603,1066

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sankey.json

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weights.R

# Optimization of weights

# optimization function
fn = function(w) {
    # results of 1st round should match:
    50000 * sum( (apply(X * w,1,sum) - results1)^2 ) +
    # results of the 2nd round should match:
    50000 * sum( (apply(X * w,2,sum) - results2)^2 ) +
    # loss function 1, the weights should not be far from 1:
    sum( c(t(w-1) %*% (w-1)) ) +
    # loss function 2, the rate shall be similar to zeman / schwarzenberg in 1st round
    # w[,1] - w[,2] did not work in optim, so workaround:
    #1.669086312/0.719913577 is rate of respondents for zeman / schwarzenberg in 1st round
    sum( (apply(w*onezero,1,sum) / apply(w*zeroone,1,sum) - 1.669086312/0.719913577)^2 )
}

# number of respondents
respondents = t(matrix(c(1661,0,553,653,141,369,201,527,0,3726,578,440,182,549,163,73,601,1062),nrow=2))
rownames(respondents) = c('zeman','fischer','sobotka','fischerova','schwarzenberg','dienstbier','roithova','bobosikova','franz')
colnames(respondents) = c('zeman2','schwarzenberg2')

#official election results
results1 = c(0.2421,0.1635,0.0246,0.0323,0.234,0.1612,0.0495,0.0239,0.0684)
results2 = c(0.5480,0.4519)

X = respondents/sum(c(respondents))

# help matrices:
onezero = matrix(c(1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0),nrow=9)
zeroone = matrix(c(0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1),nrow=9)

# starting values:
S = matrix(1,9,2)
S[1,2] = 0.1
S[5,1] = 0.1

# optimization:
optim(S,fn,control=list(maxit=20000))