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#!/usr/bin/env python
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# -*- coding:utf-8 -*-
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'''
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Step 8
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'''
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from __future__ import print_function
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from base import create_csv, TARGET_DIR, MODEL_LIST, RAW_DIR
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import os
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import csv
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COMPARSION_PAIR = [
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(0, 0), (1, 1), (4, 2), (5, 3),
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(8, 4), (10, 5), (11, 6), (13, 7),
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(15, 8), (16, 9), (17, 10), (19, 11),
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(20, 12), (22, 13), (25, 14),
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(27, 15), (28, 16), (29, 17), (31, 18),
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]
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def get_test_data(m):
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if not m:
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return []
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result = []
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lo_list = []
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fpath = os.path.join(RAW_DIR, 'LO_TestData.csv')
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with open(fpath, 'rb') as f:
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rows = csv.reader(f)
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rows.next()
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for r in rows:
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if r[1] != m.upper():
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continue
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result.append(r)
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lo_list.append(r[0])
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return (lo_list, result)
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def get_ro_data(m, suffix):
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if not m or not suffix:
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return []
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result = []
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fname = '%s-%s.csv' % (m, suffix)
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fpath = os.path.join(TARGET_DIR, 'part7', fname)
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with open(fpath, 'rb') as f:
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rows = csv.reader(f)
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for r in rows:
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result.append(r)
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return result
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def get_similarity_count(l, r):
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cnt = 0
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for (x, y) in COMPARSION_PAIR:
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r_value = r[y].replace('*', '')
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if l[x] == r_value:
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cnt += 1
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elif r_value == 'Y/N' and l[x] in ('Y', 'N'):
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cnt += 1
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return cnt
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def middleman(ls, rs):
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if not len(ls):
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return ls
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result = []
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for lo in ls:
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data = lo[:]
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for ro in rs:
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sim_count = get_similarity_count(lo[:], ro)
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data.append(sim_count)
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result.append(data)
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return result
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def main():
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header = ['LO_xxx', '____', ]
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for m in MODEL_LIST:
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l_list, lo_data = get_test_data(m)
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for i in '1234':
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m_header = header[:]
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m_header[1] = m
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ros = get_ro_data(m, i)
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for r in ros:
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m_header.append(r[0])
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result = middleman(lo_data, ros)
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output_name = '%s-%s.csv' % (m, i)
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# process header -- get ind of first R_xxx
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number_ind = 0
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cnt_ind = 0
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for i in result[0]:
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try:
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float(i)
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number_ind = cnt_ind
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cnt_ind = 0
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break
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except ValueError:
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cnt_ind += 1
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__h = m_header[:2] + ['_' for i in xrange(0, number_ind-2)] + m_header[3:]
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result = [__h] + result
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create_csv(output_name, result, directory='part8')
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main()
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