#!/usr/bin/env python
# coding: utf-8

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#check if plotly is installed version
#otherwise pip install plotly 
import plotly 

plotly.__version__


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#import matplotlib 
import matplotlib.pyplot as plt 
import numpy as np 
get_ipython().run_line_magic('matplotlib', 'inline')

# Package all mpl plotting commands inside one function
def plot_mpl_fig():
    
    # Make two time arrays
    t1 = np.arange(0.0, 2.0, 0.1)
    t2 = np.arange(0.0, 2.0, 0.01)

    # N.B. .plot() returns a list of lines.  
    # The "l1, = plot" usage extracts the first element of the list 
    # into l1 using tuple unpacking.  
    # So, l1 is a Line2D instance, not a sequence of lines
    l1, = plt.plot(t2, np.exp(-t2), label='decaying exp.')
    l2, l3 = plt.plot(t2, np.sin(2 * np.pi * t2), '--go', 
                      t1, np.log(1 + t1), '.')
    l4, = plt.plot(t2, np.exp(-t2) * np.sin(2 * np.pi * t2), 'rs-.')

    # Add axis labels and title
    plt.xlabel('time')
    plt.ylabel('volts')
    plt.title('Damped oscillation')
    
    return (l1, l2, l3, l4)  # return line objects (for legend, later)

# Plot it!
plot_mpl_fig()

#assigning current matplotlib object
#gcf stands for get current figure. 
mpl_fig1 = plt.gcf()


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#converting above matplotlib into potly 
#communicates wit plotly server 
import plotly.plotly as py

#plotly tools 
#use tls.set_credentails_file(username='yourusername' api_key='yourapikey')
#use tls.get_credentials_file() to view authentication details of plotly 
#Refer https://plot.ly/python/user-guide/ for more infor 
import plotly.tools as tls 

#Graph objects 
from plotly.graph_objs import * 

py_fig1 = tls.mpl_to_plotly(mpl_fig1,verbose=False)
#uncomment below line to view the data 
#py_fig1.to_string()
py.iplot_mpl(mpl_fig1, strip_style=True, filename='s6_damped_oscillation')


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