draw_graphs_of_training.py

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

train1 = pd.read_csv("Z:/scratch/202105171236data_Polina/nn_anopheles/dataset_like_Akita/data/Aalb_2048bp_repeat/train_out_test5_fix_random3/model_stat.txt", sep="\t")
# train2 = pd.read_csv("Z:/scratch/202105171236data_Polina/nn_anopheles/dataset_like_Akita/data/Aalb_2048bp_repeat/train_out_test2_fix_random3/model23.txt", sep=" ", names=range(24))
# train3 = pd.read_csv("Z:/scratch/202105171236data_Polina/nn_anopheles/dataset_like_Akita/data/Aalb_2048bp_repeat/train_out_test3_fix_random3/model33.txt", sep=" ", names=range(24))
# global_oe = pd.read_csv("./model_graphs/aalb_globaloe_without_x.txt", sep=" ", names=range(24))
# print(best[10])
plt.plot(train1["epoch"], np.log(train1["train_loss_epoch"]), linestyle='solid', label = 'train_loss')
plt.plot(train1["epoch"], np.log(train1["valid_loss_epoch"]), linestyle='dashed', label = 'valid_loss')
# plt.plot(train3[1], train3[15], linestyle='dashdot', label = 'train33')
# plt.plot(global_oe[1], global_oe[18], linestyle='dotted', label = 'global_oe')
plt.legend()
plt.title("train_loss_epoch")
plt.show()
# print(best)