rl_2d_walker.js/scripts/view_log.ipynb

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%pylab inline
import pandas as pd
import os
import glob

Populating the interactive namespace from numpy and matplotlib

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from pylab import rcParams
rcParams['figure.figsize'] = 10, 4

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latest_log = sorted(glob.glob('../outputs/*.log'))[-1]
latest_log

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'../outputs/train_2018-12-08_08-34-55.log'

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def parse_log(infile):
    datas = []
    data = {}
    for line in open(infile).readlines():
        if line.startswith('metric'):
            _, name, val = line.strip('\n').split(' ', 2)
            val = float(val)
            if name=='episodeSteps':
                steps=val
                if len(data): datas.append(data)
                data = {}
            data[name] = val

    df = pd.DataFrame(datas)
    df = df.set_index('steps')
    return df

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df = parse_log(latest_log)

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df['reward'].plot(style='.', title='reward')

Out [6]:

<matplotlib.axes._subplots.AxesSubplot at 0x7f516f97a518>

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df[['head_height','center_y','mean_foot_height']].plot(style='.', ylim=[-2,2])

Out [7]:

<matplotlib.axes._subplots.AxesSubplot at 0x7f516fa66198>

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df[['center_x']].plot(style='.')

Out [8]:

<matplotlib.axes._subplots.AxesSubplot at 0x7f516f972390>

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df['ActorLoss'].plot(style='.')
df['CriticLoss'].plot(style='.', secondary_y=True, ax=plt.gca())
plt.legend()

Out [9]:

<matplotlib.legend.Legend at 0x7f516fb6deb8>

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df[['head_height_reward']].plot(style='.')

Out [10]:

<matplotlib.axes._subplots.AxesSubplot at 0x7f516fb1b160>

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for col in df.columns:
    df[col].plot(style='.', title=col)
    plt.show()

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