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refactor: use if __name__ == "__main__" #65

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refactor: use if __name__ == "__main__" #65

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62dd48a
use main function
karunpoudel Apr 24, 2024
2e6a6a5
refactor
karunpoudel Apr 24, 2024
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263 changes: 142 additions & 121 deletions school_center.py
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Original file line number Diff line number Diff line change
@@ -1,9 +1,9 @@
from utils.custom_logger import configure_logging
from typing import Dict, List
from random import Random
import os
import argparse
import logging
import random
import csv
import math

Expand All @@ -17,6 +17,10 @@
configure_logging()
logger = logging.getLogger(__name__)

random = Random()
allocations = {} # to track mutual allocations
prefs = {} # preference score for the given school and center


def create_dir(dirPath: str):
"""
Expand All @@ -36,7 +40,7 @@ def haversine_distance(lat1, lon1, lat2, lon2):
# Convert decimal degrees to radians
lat1, lon1, lat2, lon2 = map(math.radians, [lat1, lon1, lat2, lon2])

# Haversine formula
# Haversine formula
dlon = lon2 - lon1
dlat = lat2 - lat1
a = math.sin(dlat/2)**2 + math.cos(lat1) * math.cos(lat2) * math.sin(dlon/2)**2
Expand All @@ -55,12 +59,12 @@ def centers_within_distance(school: Dict[str, str], centers: Dict[str, str], dis

"""
def center_to_dict(c, distance):
return {'cscode': c['cscode'],
'name': c['name'],
'address': c['address'],
'capacity': c['capacity'],
'lat': c['lat'],
'long': c['long'],
return {'cscode': c['cscode'],
'name': c['name'],
'address': c['address'],
'capacity': c['capacity'],
'lat': c['lat'],
'long': c['long'],
'distance_km': distance}

def sort_key(c):
Expand Down Expand Up @@ -149,7 +153,7 @@ def calc_per_center(count: int) -> int:
return 100
# elif count <= 900:
# return 200
else:
else:
return 200


Expand Down Expand Up @@ -178,123 +182,140 @@ def is_allocated(scode1: str, scode2: str) -> bool:
return allocations.get(scode1, {}).get(scode2) is not None


parser = argparse.ArgumentParser(
prog='center randomizer',
description='Assigns centers to exam centers to students')
parser.add_argument('schools_tsv', default='schools.tsv',
help="Tab separated (TSV) file containing school details")
parser.add_argument('centers_tsv', default='centers.tsv',
help="Tab separated (TSV) file containing center details")
parser.add_argument('prefs_tsv', default='prefs.tsv',
help="Tab separated (TSV) file containing preference scores")
parser.add_argument(
'-o', '--output', default='school-center.tsv', help='Output file')
parser.add_argument('-s', '--seed', action='store', metavar='SEEDVALUE',
default=None, type=float,
help='Initialization seed for Random Number Generator')

args = parser.parse_args()

random = random.Random(args.seed) #overwrites the random module to use seeded rng

schools = sorted(read_tsv(args.schools_tsv), key= school_sort_key)
centers = read_tsv(args.centers_tsv)
centers_remaining_cap = {c['cscode']: int(c['capacity']) for c in centers}
prefs = read_prefs(args.prefs_tsv)

remaining = 0 # stores count of non allocated students
allocations = {} # to track mutual allocations

OUTPUT_DIR = 'results/'
create_dir(OUTPUT_DIR) # Create the output directory if not exists
with open('{}school-center-distance.tsv'.format(OUTPUT_DIR), 'w', encoding='utf-8') as intermediate_file, \
open(OUTPUT_DIR + args.output, 'w', encoding='utf-8') as a_file:
writer = csv.writer(intermediate_file, delimiter="\t")
writer.writerow(["scode",
"s_count",
"school_name",
"school_lat",
"school_long",
"cscode",
"center_name",
"center_address",
"center_capacity",
"distance_km"])

allocation_file = csv.writer(a_file, delimiter='\t')
allocation_file.writerow(["scode",
"school",
"cscode",
"center",
"center_address",
"allocation",
"distance_km"])

for s in schools:
centers_for_school = centers_within_distance(
s, centers, PREF_DISTANCE_THRESHOLD)
to_allot = int(s['count'])
per_center = calc_per_center(to_allot)

allocated_centers = {}

# per_center = math.ceil(to_allot / min(calc_num_centers(to_allot), len(centers_for_school)))
for c in centers_for_school:
writer.writerow([s['scode'],
s['count'],
s['name-address'],
s['lat'],
s['long'],
c['cscode'],
c['name'],
c['address'],
c['capacity'],
c['distance_km']])
if is_allocated(c['cscode'], s['scode']):
continue
next_allot = min(to_allot, per_center, max(
centers_remaining_cap[c['cscode']], MIN_STUDENT_IN_CENTER))
if to_allot > 0 and next_allot > 0 and centers_remaining_cap[c['cscode']] >= next_allot:
allocated_centers[c['cscode']] = c
allocate(s['scode'], c['cscode'], next_allot)
# allocation.writerow([s['scode'], s['name-address'], c['cscode'], c['name'], c['address'], next_allot, c['distance_km']])
to_allot -= next_allot
centers_remaining_cap[c['cscode']] -= next_allot

if to_allot > 0: # try again with relaxed constraints and more capacity at centers
expanded_centers = centers_within_distance(
s, centers, ABS_DISTANCE_THRESHOLD)
for c in expanded_centers:
def randomize(
*,
schools_tsv: str,
centers_tsv: str,
prefs_tsv: str,
output: str,
seed: float = None
):
if seed:
random.seed(seed)

schools = sorted(read_tsv(schools_tsv), key= school_sort_key)
centers = read_tsv(centers_tsv)
centers_remaining_cap = {c['cscode']: int(c['capacity']) for c in centers}
prefs.update(read_prefs(prefs_tsv))

remaining = 0 # stores count of non allocated students

OUTPUT_DIR = 'results/'
create_dir(OUTPUT_DIR) # Create the output directory if not exists
with open('{}school-center-distance.tsv'.format(OUTPUT_DIR), 'w', encoding='utf-8') as intermediate_file, \
open(OUTPUT_DIR + output, 'w', encoding='utf-8') as a_file:
writer = csv.writer(intermediate_file, delimiter="\t")
writer.writerow(["scode",
"s_count",
"school_name",
"school_lat",
"school_long",
"cscode",
"center_name",
"center_address",
"center_capacity",
"distance_km"])

allocation_file = csv.writer(a_file, delimiter='\t')
allocation_file.writerow(["scode",
"school",
"cscode",
"center",
"center_address",
"allocation",
"distance_km"])

for s in schools:
centers_for_school = centers_within_distance(
s, centers, PREF_DISTANCE_THRESHOLD)
to_allot = int(s['count'])
per_center = calc_per_center(to_allot)

allocated_centers = {}

# per_center = math.ceil(to_allot / min(calc_num_centers(to_allot), len(centers_for_school)))
for c in centers_for_school:
writer.writerow([s['scode'],
s['count'],
s['name-address'],
s['lat'],
s['long'],
c['cscode'],
c['name'],
c['address'],
c['capacity'],
c['distance_km']])
if is_allocated(c['cscode'], s['scode']):
continue
stretched_capacity = math.floor(
int(c['capacity']) * STRETCH_CAPACITY_FACTOR + centers_remaining_cap[c['cscode']])
next_allot = min(to_allot, max(
stretched_capacity, MIN_STUDENT_IN_CENTER))
if to_allot > 0 and next_allot > 0 and stretched_capacity >= next_allot:
next_allot = min(to_allot, per_center, max(
centers_remaining_cap[c['cscode']], MIN_STUDENT_IN_CENTER))
if to_allot > 0 and next_allot > 0 and centers_remaining_cap[c['cscode']] >= next_allot:
allocated_centers[c['cscode']] = c
allocate(s['scode'], c['cscode'], next_allot)
# allocation.writerow([s['scode'], s['name-address'], c['cscode'], c['name'], c['address'], next_allot, c['distance_km']])
to_allot -= next_allot
centers_remaining_cap[c['cscode']] -= next_allot

for c in allocated_centers.values():
allocation_file.writerow([s['scode'],
s['name-address'],
c['cscode'],
c['name'],
c['address'],
allocations[s['scode']][c['cscode']],
c['distance_km']])

if to_allot > 0:
remaining += to_allot
logger.warn(
f"{to_allot}/{s['count']} left for {s['scode']} {s['name-address']} centers: {len(centers_for_school)}")

logger.info("Remaining capacity at each center (remaining_capacity cscode):")
logger.info(sorted([(v, k)
for k, v in centers_remaining_cap.items() if v != 0]))
logger.info(
f"Total remaining capacity across all centers: {sum({k:v for k, v in centers_remaining_cap.items() if v != 0}.values())}")
logger.info(f"Students not assigned: {remaining}")
if to_allot > 0: # try again with relaxed constraints and more capacity at centers
expanded_centers = centers_within_distance(
s, centers, ABS_DISTANCE_THRESHOLD)
for c in expanded_centers:
if is_allocated(c['cscode'], s['scode']):
continue
stretched_capacity = math.floor(
int(c['capacity']) * STRETCH_CAPACITY_FACTOR + centers_remaining_cap[c['cscode']])
next_allot = min(to_allot, max(
stretched_capacity, MIN_STUDENT_IN_CENTER))
if to_allot > 0 and next_allot > 0 and stretched_capacity >= next_allot:
allocated_centers[c['cscode']] = c
allocate(s['scode'], c['cscode'], next_allot)
# allocation.writerow([s['scode'], s['name-address'], c['cscode'], c['name'], c['address'], next_allot, c['distance_km']])
to_allot -= next_allot
centers_remaining_cap[c['cscode']] -= next_allot

for c in allocated_centers.values():
allocation_file.writerow([s['scode'],
s['name-address'],
c['cscode'],
c['name'],
c['address'],
allocations[s['scode']][c['cscode']],
c['distance_km']])

if to_allot > 0:
remaining += to_allot
logger.warning(
f"{to_allot}/{s['count']} left for {s['scode']} {s['name-address']} centers: {len(centers_for_school)}")

logger.info("Remaining capacity at each center (remaining_capacity cscode):")
logger.info(sorted([(v, k)
for k, v in centers_remaining_cap.items() if v != 0]))
logger.info(
f"Total remaining capacity across all centers: {sum({k:v for k, v in centers_remaining_cap.items() if v != 0}.values())}")
logger.info(f"Students not assigned: {remaining}")


if __name__ == "__main__":
parser = argparse.ArgumentParser(
prog='center randomizer',
description='Assigns centers to exam centers to students')
parser.add_argument('schools_tsv', default='schools.tsv',
help="Tab separated (TSV) file containing school details")
parser.add_argument('centers_tsv', default='centers.tsv',
help="Tab separated (TSV) file containing center details")
parser.add_argument('prefs_tsv', default='prefs.tsv',
help="Tab separated (TSV) file containing preference scores")
parser.add_argument(
'-o', '--output', default='school-center.tsv', help='Output file')
parser.add_argument('-s', '--seed', action='store', metavar='SEEDVALUE',
default=None, type=float,
help='Initialization seed for Random Number Generator')

args = parser.parse_args()
randomize(
schools_tsv=args.schools_tsv,
centers_tsv=args.centers_tsv,
prefs_tsv=args.prefs_tsv,
output=args.output,
seed=args.seed
)