In [1]:

    

import pandas as pd
from pandas.io.json import json_normalize #package for flattening json in pandas df
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
import json
import os
%matplotlib inline


    

In [2]:

    

os.chdir("./runs/lagaris/1d_trapz/")
origin_path = os.getcwd() 
runs_id = os.listdir("./")
runs_id = [int(item) for item in runs_id]
runs_id = sorted(runs_id)


    

In [3]:

    

df_list = []
for run_id in runs_id:
    os.chdir("./"+str(run_id))
    f_in = open('out.json', 'r')
    run_info = json.load(f_in)
    f_in.close()
    a = json_normalize(run_info)
    #a.set_index(pd.Index([run_id]))
    df_list.append(a)
    #a = pd.concat(a,b)
    os.chdir(origin_path)
res1 = pd.concat(df_list,ignore_index=True)


    

In [4]:

    

res = res1[res1['Model info.m_train'] == 30]
plt.figure(figsize=(15,10))
plt.grid(True)
plt.title('MSE vs m_trapz', fontsize=26)
plt.xlabel('Number of integration points', fontsize=20)
plt.ylabel('MSE', fontsize=20)
res.plot(
    x='Model info.m_trapz',
    y='Out info.MSE',
    logy=True,
    logx=True,
    ax = plt.gca(),
    style = 'ro--',
)

plt.gca().legend(
   loc='best',
   fontsize=26
)


    

    
Out[4]:





<matplotlib.legend.Legend at 0x1bcee936cc0>