import os
import pandas as pd
import numpy as np
from pathlib import Path
from module.simulator import Simulator
simulator = Simulator()
submission_ini = pd.read_csv(
os.path.join(Path(__file__).resolve().parent, 'sample_submission.csv'))
order_ini = pd.read_csv(
os.path.join(Path(__file__).resolve().parent, 'order.csv'))
class Genome():
def __init__(self,
score_ini,
input_len,
output_len_1,
output_len_2,
h1=50,
h2=50,
h3=50):
# 평가 점수 초기화
self.score = score_ini
# 히든레이어 노드 개수
self.hidden_layer1 = h1
self.hidden_layer2 = h2
self.hidden_layer3 = h3
# Event 신경망 가중치 생성
# Recording the remaining BLK stock to `blk_diffs`
blk_diffs.append(stock.loc[stock_idx, blk_type])
# Calculating the score
def f_xa(x, a):
return 1 - (x / a) if x < a else 0
N = order.iloc[:, 1:].sum().sum()
p = sum([abs(blk_diff) for blk_diff in blk_diffs if blk_diff < 0])
q = sum([blk_diff for blk_diff in blk_diffs if blk_diff > 0])
score = 50 * f_xa(p, 10 * N) + 20 * f_xa(q, 10 * N) + 30
return score, stock
if __name__ == "__main__":
import timeit
from module.simulator import Simulator as Old_Simulator
sample = pd.read_csv("Dacon_baseline.csv")
sim = Simulator()
start_time = timeit.default_timer()
score, stock = sim.get_score(sample)
print("new simulator time :", timeit.default_timer() - start_time)
old_sim = Old_Simulator()
start_time = timeit.default_timer()
old_score, old_stock = old_sim.get_score(sample)
print("old simulator time :", timeit.default_timer() - start_time)