In [1]:

    

import matplotlib.pyplot as plt
import plotly
import plotly.offline as offline
offline.init_notebook_mode()
import plotly.graph_objs as go
import tensorflow as tf
import numpy as np


    

In [8]:

    

import plotly.offline as offline
offline.init_notebook_mode()
import plotly.graph_objs as go


    

In [10]:

    

events = '../summary/DS-MNIST_nz5_nc5_infoTrue_19_45_38_20161218/events.out.tfevents.1482108340.fnd'


    

In [11]:

    

kcx = []
for e in tf.train.summary_iterator(events):
    for v in e.summary.value:
        if v.tag == 'KLD q(c|x) || p(z)':
            kcx.append(v.simple_value)
kcx = np.array(kcx)


    

In [8]:

    

kcx


    

    
Out[8]:





array([], dtype=float64)

In [17]:

    

import plotly.offline as offline
offline.init_notebook_mode()
import plotly.graph_objs as go
import plotly.plotly as py

trace1 = go.Scatter(
    y=kcx[::30],
    mode='lines+markers',
    name="'spline'",
    text=["tweak line smoothness<br>with 'smoothing' in line object"],
    hoverinfo='text+name',
    line=dict(
        shape='spline'
    )
)
data = [trace1]

fig = dict(data=data, layout=layout)
offline.iplot(fig, filename='line-shapes')