In [1]:

    

#import necessary python libraries
import json
import matplotlib.pyplot as plt
import numpy as np
from scipy.optimize import curve_fit
import pandas as pd
import math
from JSON_to_DF import JSON_to_DataFrame
from Lightcurve_class import *
%matplotlib inline


    

In [3]:

    

#Load data into a pandas dataframe for easier manipulation
df = JSON_to_DataFrame("../../../OSC_data/JSON_data/SN2011fe.json")

#Pick out the I band portion of data 
I_data = df[df.band == 'I']

#Create instance of Lightcurve class passing data as magnitude
data = filter_lightcurve(I_data.time.values, I_data.magnitude.values, I_data.e_magnitude.values, 'I', 'mag')


    

    




/Users/ethanmarx/anaconda/envs/NUREU17/lib/python3.6/site-packages/pandas/core/generic.py:1299: PerformanceWarning: 
your performance may suffer as PyTables will pickle object types that it cannot
map directly to c-types [inferred_type->mixed,key->block1_values] [items->['band', 'source', 'telescope']]

  return pytables.to_hdf(path_or_buf, key, self, **kwargs)






    




---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-3-62428e6c142c> in <module>()
      6 
      7 #Create instance of Lightcurve class passing data as magnitude
----> 8 data = filter_lightcurve(I_data.time.values, I_data.magnitude.values, I_data.e_magnitude.values, 'I', 'mag')
      9 

TypeError: __init__() missing 1 required positional argument: 'path'

In [3]:

    

#Fit data to Kapernka model and return RMSE
print(data.Kapernka_fit_plot())
plt.xlabel('time (days)')
plt.ylabel('relative flux')
plt.title('Kapernka model')


    

    













    




20.0501435443






    
Out[3]:





<matplotlib.text.Text at 0x11cd34c10>






    

In [4]:

    

#Fit data to polynomial function of any degree 
plt.close()
print(data.polynomial_fit_plot(10))


    

    













    




767.363686656

In [5]:

    

plt.close()
print(data.Bazin_fit_plot())
plt.title('Bazin Model')


    

    













    




19.6523518991






    
Out[5]:





<matplotlib.text.Text at 0x11c41c550>






    

In [5]:

    

temp =df[['band', 'source']]


    

In [ ]:

    




    

In [6]:

    

pairs = []
for row in temp.iterrows():
    if(pd.isnull(row[1]['band'])):
        continue
    element = (row[1]['band'], row[1]['source'])
    if(element not in pairs):
        pairs.append(element)
pairs


    

    
Out[6]:





[("g'", '25,31'),
 ('W1', '9'),
 ('U', '9'),
 ('B', '9'),
 ('V', '9'),
 ('B', '13,31'),
 ('I', '13,31'),
 ('R', '13,31'),
 ('V', '13,31'),
 ('U', '13,31'),
 ('B', '12'),
 ('Rc', '12'),
 ('V', '12'),
 ('W2', '9'),
 ('M2', '9'),
 ('B', '19,31'),
 ('I', '19,31'),
 ('R', '19,31'),
 ('V', '19,31'),
 ('Ic', '12')]

In [ ]:

    




    

In [18]:

    

Lightcurves = {}
for x in pairs:
    data = df[df.band == x[0]]
    data = data[data.source == x[1]]
    label = str(x[0]) + '_' + str(x[1])
    Lightcurves[label] = filter_lightcurve(data.time.values, data.magnitude.values, data.e_magnitude.values, str(x[0]))
    print x[1].split(',')


    

    




---------------------------------------------------------------------------
IndexError                                Traceback (most recent call last)
<ipython-input-18-f2933093c03b> in <module>()
      5     label = str(x[0]) + '_' + str(x[1])
      6     Lightcurves[label] = filter_lightcurve(data.time.values, data.magnitude.values, data.e_magnitude.values, str(x[0]))
----> 7     print x[1].split(',')[1]

IndexError: list index out of range

In [2]:

    

x = Supernovae("../../../OSN_data/JSON_data/SN2011fe.json")


    

In [4]:

    

x.load_LightCurves()

x.meta_data()
x.references


    

    
Out[4]:





[u'4']

In [ ]: