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import pandas
import random
from scipy.interpolate import interp1d
from typing import Literal
def get_next_difficulty(difficulty, do_increase: Literal[True, False] = True):
if do_increase:
if difficulty >= 0.95:
next_difficulty = round(random.uniform(0.95, 0.99), 2)
else:
next_difficulty = round(random.uniform(difficulty + 0.01, difficulty + 0.05), 2)
else:
if difficulty <= 0.05:
next_difficulty = round(random.uniform(0.01, 0.05), 2)
else:
next_difficulty = round(random.uniform(difficulty - 0.05, difficulty - 0.01), 2)
return next_difficulty
def generate_start_step(difficulty: float, path_to_csv_file: str = "data.csv"):
"""generate start and step values interpolating results to function built from data from file"""
df = pandas.read_csv(path_to_csv_file, delimiter=',', header=0, names=['difficulty', 'start'])
all_rows = df.loc[:]
difficulties = [row_data['difficulty'] for _, row_data in all_rows.iterrows()]
starts = [row_data['start'] for _, row_data in all_rows.iterrows()]
interp_start_func = interp1d(difficulties, starts)
generated_start = round(float(interp_start_func(difficulty)))
if difficulty <= 0.3:
step = 1
elif difficulty > 0.6:
step = 10
else:
step = 5
return (generated_start, step)
def convert_sequence_to_string(start, step, sep=", "):
stop = start + 3 * step
return sep.join([str(num) for num in range(start, stop, step)]) |