# -*- coding: utf-8 -*-
# aalen additive
if __name__ == "__main__":
import pandas as pd
import numpy as np
import time
from lifelines import LogNormalFitter
np.random.seed(1)
N = 250000
mu = 3 * np.random.randn()
sigma = np.random.uniform(0.1, 3.0)
X, C = np.exp(sigma * np.random.randn(N) +
mu), np.exp(np.random.randn(N) + mu)
E = X <= C
T = np.minimum(X, C)
lnf = LogNormalFitter()
start_time = time.time()
lnf.fit(T, E)
print("--- %s seconds ---" % (time.time() - start_time))
lnf.print_summary(5)
plot_hist(uptime, obs_up, 99, weib)
plt.title(f'Probability of failure in time [general]'#, reasons: ' + ', '.join([str(x) for x in reasons_relative])
)
plt.savefig(rf'./{file_used.split(".")[0]}/figures/fail_prob_{file_used.split(".")[0]}_general.pdf', dpi=2400, layout='tight')
plt.savefig(rf'./{file_used.split(".")[0]}/figures/fail_prob_{file_used.split(".")[0]}_general.png', dpi=2400, layout='tight')
plt.close()
# GENERATE REPAIR TIME DEFINITION
# Generate a lognormal distribution for the repair time
print('Repair time')
print(len('Repair time') * '-')
lnf = LogNormalFitter()
try:
lnf.fit(downtime, obs_down)
logn = Lognormal(lnf.sigma_, lnf.mu_)
except:
raise
if print_all:
print(logn)
if export_all:
repair_dist = ET.SubElement(root, 'repair_dist')
repair_dist.text = 'lognormal'
repair_dist.set("sigma", str(lnf.sigma_))
repair_dist.set("mu", str(lnf.mu_))
repair_dist.set("mean", str(logn.mean_time()))
plot_hist(downtime, obs_down, 99, logn)
plt.title(f"Probability of repair in time"#, reasons: {', '.join([str(x) for x in reasons_relative])}"
)
plt.savefig(rf'./{file_used.split(".")[0]}/figures/fail_prob_{file_used.split(".")[0]}_repair.pdf', dpi=2400, layout='tight')
