1#! usr/bin/env python
  2"""
  3Determine a board for a committee from a set of votes
  4"""
  5import sys
  6import argparse
  7import logging
  8from math import floor
  9import pandas as pd
 10
 11logging.basicConfig(
 12    format="\x1b[33;20m[%(levelname)s] %(name)s:%(funcName)s:%(lineno)d\033[0m %(message)s",
 13    level=logging.INFO)
 14LOG = logging.getLogger("vote_tally")
 15
 16def winner(total_votes,min_votes_req,show_order=False):
 17    """
 18    # Tells you the elected candidate for a role
 19
 20    This gives the name of the candidate who reached the minimum
 21    number of votes necessary to be elected, or the bool False
 22    if nobody has won yet.
 23
 24    Parameters
 25    ----------
 26    total_votes : pandas dataframe
 27        Dataframe of candidates and the amount of votes they have
 28    min_votes_req : int
 29        The minimum number of votes required to be elected
 30
 31    Returns
 32    -------
 33    candidate : string
 34        The name of the elected candidate.
 35        Returns with the bool False if there is not yet a winner.
 36    """
 37    winners = total_votes[total_votes['votes']>=min_votes_req]['candidate'].values
 38    if len(winners) == 0:
 39        return False
 40    if len(winners) == 1:
 41        if show_order:
 42            LOG.info(f"Final candidates:\n{total_votes[total_votes['votes']>0]}")
 43        return winners[0]
 44    sys.exit('You have two winners:'+str(winners))
 45
 46def tidy(votes):
 47    """
 48    # Tidies the ballots
 49
 50    Ensures every ballot starts at 1 and goes up from there
 51    Also ensure no ranks are negative
 52
 53    Parameters
 54    ----------
 55    votes : pandas dataframe
 56        Every column is a candidate. Every row is one ballot and
 57        the preferential order for their votes.
 58
 59    Returns
 60    -------
 61    votes : pandas dataframe
 62        Every column is a candidate. Every row is one ballot and
 63        the preferential order for their votes.
 64        Now all ballots are properly formatted.
 65    """
 66    votes[votes<0] = 0
 67    for _, row in votes.iterrows():
 68        if max(row) > 1:
 69            row_values = list(row[row>0].values)
 70            row_values.sort()
 71            replacements = range(1,len(row_values)+1)
 72            for row_value, replacement in zip(row_values,replacements):
 73                row[row==row_value] = replacement
 74    votes[votes<0] = 0
 75    return votes
 76
 77def remove_lowest(votes,show_order=False):
 78    """
 79    # Removes the least-votes candidate and redistributes
 80
 81    Using the single-transferrable-vote method, the candidate
 82    with the fewest first-place votes is removed from the
 83    election and the votes for them redistributed.
 84
 85    We find those ballots which list said candidate
 86    first, then redistribute those votes by subtracting 1 from
 87    every element in the vote order until there is a new 1st
 88    ranked vote per ballot. Also, all votes for the removed
 89    candidated are removed.
 90
 91    Thus, for those affected ballots, their no. 2 choice
 92    becomes their no. 1 choice, and so on.
 93
 94    Parameters
 95    ----------
 96
 97    total_votes : pandas dataframe
 98        Dataframe of candidates and the amount of votes they have
 99    votes : pandas dataframe
100        Every column is a candidate. Every row is one ballot and
101        the preferential order for their votes.
102
103    Returns
104    -------
105    votes : pandas dataframe
106        Every column is a candidate. Every row is one ballot and
107        the preferential order for their votes.
108        Now the worst-performing candidate has been removed.
109
110    """
111
112    candidates = list(votes.columns)
113    removable_candidates = candidates
114
115    for rank in range(1,max(votes.values[0])+1):
116
117        total_votes = count_total_votes(votes[removable_candidates],rank=rank)
118        if max(total_votes['votes'])==0:
119            continue
120
121        lowest_votes = min(total_votes[total_votes['votes']>0]['votes'])
122        lowest_candidates = total_votes[total_votes['votes']==lowest_votes]['candidate'].values
123
124        if len(lowest_candidates) == 1:
125            votes[votes[lowest_candidates[0]]==1]-=1
126            votes[lowest_candidates[0]] = 0
127            votes = tidy(votes)
128            if show_order:
129                LOG.info(f"Removed: {lowest_candidates[0]}")
130            return votes
131
132        removable_candidates = lowest_candidates
133    if show_order:
134        LOG.info(f"Final candidates:\n{total_votes[total_votes['votes']>0]}")
135    sys.exit('No more votes to redistribute but no winners')
136
137def count_total_votes(votes,rank=1):
138    """
139    # Count how many votes each candidate has
140
141    Parameters
142    ----------
143    votes : pandas dataframe
144        Every column is a candidate. Every row is one ballot and
145        the preferential order for their votes.
146
147    Returns
148    -------
149    total_votes : pandas dataframe
150        Dataframe of candidates and the amount of votes they have
151    """
152    candidates = list(votes.columns)
153    votes_count = []
154    for candidate in candidates:
155        votes_count.append(len(votes[votes[candidate]==rank]))
156    total_votes = pd.DataFrame({'candidate':candidates,'votes':votes_count})
157    return total_votes
158
159def first_algorithm(votes,show_order=False,people=1):
160    """
161    # Calculates the elected candidate for a role
162
163    Parameters
164    ----------
165    votes : pandas dataframe
166        Every column is a candidate. Every row is one ballot and
167        the preferential order for their votes.
168
169    Returns
170    -------
171    winner : string
172        The succesfully elected candidate
173    """
174
175    votes = verify(votes) # remove invalid votes
176    n_voters = len(votes)
177    min_votes_req = int(floor(n_voters/(people+1))+1)
178    total_votes = count_total_votes(votes)
179
180    LOG.debug(f"initial votes = \n{votes}")
181    LOG.debug(f"initial total_votes = \n{total_votes}")
182
183    while not winner(total_votes,min_votes_req,show_order=show_order):
184        votes = remove_lowest(votes,show_order=show_order)
185        total_votes = count_total_votes(votes)
186        LOG.debug(f"current votes = \n{votes}")
187        LOG.debug(f"current total_votes = \n{total_votes}")
188    return winner(total_votes,min_votes_req)
189
190def read_votes(input_file):
191    """
192    # Read votes in from a csv file into a data frame
193    """
194
195    votes_df = pd.read_csv(input_file, dtype=float)
196
197    return votes_df
198
199def verify(votes):
200    """
201    Removes any invalid votes from the collected votes.
202    Valid votes include every number is sequential,
203    between 1 and number of votes, no repeated numbers and
204    a vote made for every candidate.
205
206    Parameters
207    ----------
208    votes : pandas dataframe
209        Every column is a candidate. Every row is one ballot and
210        the preferential order for their votes.
211
212    Returns
213    -------
214    verified_votes : pandas dataframe
215        Dataframe of only votes which are valid
216    """
217
218    n_votes = votes.shape[0] # Number of votes
219    n_candids = votes.shape[1] # Number of candiates
220    idx_drop = [] # Indices that are invalid and will be dropped
221
222    for i in range(n_votes):
223        # Votes for voter i
224        v_i = votes[i:i+1].values[0]
225
226        # Check that voter has voted for each candidate
227        # Each vote must be unique
228        for j in range(1,n_candids+1):
229            # Vote is invalid, break
230            if not j in v_i:
231                idx_drop.append(i)
232                break
233
234    # Drop invalid votes and return only valid votes
235    verified_votes = votes.drop(index=(idx_drop))
236    verified_votes = verified_votes.astype(int)
237    LOG.info("Dropped "+str(len(idx_drop))+" invalid ballot(s)")
238    LOG.debug("ID(s) of Invalid ballots are: "+str(idx_drop))
239
240    return verified_votes
241
242def main():
243    """
244    # Reports the winner of the election from test data
245    """
246    parser = argparse.ArgumentParser(
247            description='Determine the winner of an election')
248    parser.add_argument('-i','--input',
249        type=str,
250        default='data/test_votes.csv',
251        help='Input location of votes csv file')
252    parser.add_argument('-v','--verbose',action='store_true',help='Enable debug logging')
253    parser.add_argument('--order',action='store_true',help='Show candidate order')
254    args = parser.parse_args()
255
256    # configure logger
257    if args.verbose:
258        LOG.setLevel(logging.DEBUG)
259
260    votes_df = read_votes(args.input)
261    output = first_algorithm(votes_df,show_order=args.order)
262    LOG.info(f"The winner is: {output}")
263
264if __name__ == "__main__":
265    main()