You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
90 lines
2.5 KiB
90 lines
2.5 KiB
''' |
|
Step 4 |
|
''' |
|
# -*- coding:utf-8 -*- |
|
#!/usr/bin/env python |
|
from __future__ import print_function |
|
from base import Lo, create_csv, TARGET_DIR |
|
import os |
|
import csv |
|
import sys |
|
|
|
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 get_match_all(): |
|
result = {} |
|
fpath = os.path.join(TARGET_DIR, 'part3', 'step3_match_all.csv') |
|
with open(fpath, 'rb') as f: |
|
rows = csv.reader(f) |
|
for r in rows: |
|
result[r[0]] = r[1].split(',') |
|
return result |
|
|
|
|
|
def get_weight(xmodel): |
|
result = {} |
|
fpath = os.path.join(TARGET_DIR, 'part2', '%s-3.csv' % xmodel) |
|
with open(fpath, 'rb') as f: |
|
rows = csv.reader(f) |
|
for r in rows: |
|
result[r[0]] = [r[1], r[2], r[3], r[4], r[5], r[6]] |
|
return result |
|
|
|
|
|
def get_x_from_step3_all(m): |
|
''' |
|
July 1 requested |
|
''' |
|
fpath = os.path.join(TARGET_DIR, 'part3', '%s-all.csv' % m) |
|
los = {} |
|
with open(fpath, 'rb') as f: |
|
rows = csv.reader(f) |
|
for r in rows: |
|
for lo in r[1].split(','): |
|
los[lo] = r[0] |
|
return los |
|
|
|
|
|
def produce(match_all): |
|
for ii in xmodels.keys(): |
|
rows = [] |
|
# prepare for data --> July 1 request |
|
step_3_data = get_x_from_step3_all(ii) |
|
weight = get_weight(ii) |
|
for lo in sorted(los.los): |
|
is_matched = 1 if ii.lower() == los.los[lo]['model'].lower() else 0 |
|
# [July 1] some lo doesn't have that data, blank then |
|
july_1_col = step_3_data[lo] if lo in step_3_data else '' |
|
no_of_tree = '4Ts' if july_1_col == '4/4' else \ |
|
'3Ts' if july_1_col == '3/4' else \ |
|
'2Ts' if july_1_col == '2/4' else '1Ts' |
|
r = [no_of_tree, lo, is_matched, los.los[lo]['weight']] |
|
try: |
|
r += weight[lo] |
|
rows.append(r) # this will append only LO w/ weight |
|
except KeyError: |
|
# print(ii, ' = ', is_matched, ' / ', lo) |
|
pass |
|
_f = '%s-step4.csv' % ii |
|
create_csv(_f, rows, directory='part4') |
|
|
|
|
|
def main(*argv): |
|
ma_data = get_match_all() |
|
produce(ma_data) |
|
|
|
|
|
if __name__ == '__main__': |
|
if len(sys.argv) > 1: |
|
main(sys.argv[1:]) |
|
else: |
|
main()
|
|
|