lo-ranking/s3.py

#!/usr/bin/env python
# -*- coding:utf-8 -*-
'''
Step 3
'''
from __future__ import print_function
from base import Lo, create_csv, TARGET_DIR
import os
import csv
import sys
from s2 import RANK_ORDER

los = Lo()

xmodels = {
    'IMSf': {}, 'IMSD': {}, 'IMHf': {}, 'IMHD': {}, 'IFSf': {}, 'IFSD': {},
    'IFHf': {}, 'IFHD': {}, 'CMSf': {}, 'CMSD': {}, 'CMHf': {}, 'CMHD': {},
    'CFSf': {}, 'CFSD': {}, 'CFHf': {}, 'CFHD': {}, 'PMSf': {}, 'PMSD': {},
    'PMHf': {}, 'PMHD': {}, 'PFSf': {}, 'PFSD': {}, 'PFHf': {}, 'PFHD': {},
}
fs = ('Case1_LS.csv', 'Case1_Gender.csv', 'Case1_Level.csv', 'Case1_SciF.csv')


def process_s2_data():
    '''
    docstring huhu?
    '''
    xm_data = {}
    for ii in xmodels.keys():
        fname = '%s-2.csv' % ii
        fpath = os.path.join(TARGET_DIR, 'part2', fname)
        with open(fpath, 'rb') as f:
            rows = csv.reader(f)
            rank = 0
            for r in rows:
                if r[1] == "rank":
                    rank = r[2]
                    continue
                if ii not in xm_data:
                    xm_data[ii] = {'all': set()}
                if rank not in xm_data[ii]:
                    xm_data[ii][rank] = {}
                if r[0] not in xm_data[ii][rank]:
                    xm_data[ii][rank][r[0]] = []
                xm_data[ii][rank][r[0]] = r[1].split(',')
                xm_data[ii]['all'] = xm_data[ii]['all'].union(set(r[1].split(',')))
    return xm_data


def produce_match_all(xdata):
    rows = []
    for ii in xmodels.keys():
        _los = set()
        for _rank in xdata[ii]:
            for i in ii:
                if i in xdata[ii][_rank]:
                    _los = _los.union(set(xdata[ii][_rank][i]))
        rows.append([ii, ','.join(sorted(list(_los)))])
    _f = 'step3_match_all.csv'
    create_csv(_f, rows, directory='part3')


def produce_match_all_mra(xdata):
    for ii in xmodels.keys():
        lo_count = {}
        for j in xdata[ii]['all']:
            if j not in lo_count:
                lo_count[j] = 0
                for i in ii:
                    for rank in RANK_ORDER:
                        if rank in xdata[ii] and i in xdata[ii][rank] \
                                and j in xdata[ii][rank][i]:
                            lo_count[j] += 1
        rows = []
        max_count = len(RANK_ORDER)
        for n in xrange(max_count, 0, -1):
            rows.append([
                '%s/%s' % (n, max_count),
                ','.join([k for (k, v) in lo_count.items() if v == n])
            ])
        _f = '%s-all.csv' % (ii,)
        create_csv(_f, rows, directory='part3')


def produce_match_rank_mra(xdata, rank):
    for ii in xmodels.keys():
        lo_count = {}
        for j in xdata[ii]['all']:
            if j not in lo_count:
                lo_count[j] = 0
                for i in ii:
                    if rank in xdata[ii] and i in xdata[ii][rank] and \
                            j in xdata[ii][rank][i]:
                        lo_count[j] += 1
        rows = []
        max_count = len(RANK_ORDER)
        for n in xrange(max_count, 0, -1):
            rows.append([
                '%s/%s' % (n, max_count),
                ','.join([k for (k, v) in lo_count.items() if v == n])
            ])
        _f = '%s-rank-%s.csv' % (ii, rank)
        create_csv(_f, rows, directory='part3')


def main(*argv):
    xmm = process_s2_data()
    produce_match_all(xmm)
    produce_match_all_mra(xmm)
    for i in RANK_ORDER:
        produce_match_rank_mra(xmm, i)


if __name__ == '__main__':
    if len(sys.argv) > 1:
        main(sys.argv[1:])
    else:
        main()