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

# In[1]:


# Display graphics inline with the notebook
get_ipython().run_line_magic('matplotlib', 'inline')

# Standard Python modules
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import pandas as pd
import os
import datetime

# Module to enhance matplotlib plotting
import seaborn
seaborn.set()

# Modules to display images and data tables
from IPython.display import Image
from IPython.core.display import display

# Data Directory
dir = './data/'

# Styles
from IPython.core.display import HTML
HTML(open("styles/custom.css", "r").read())


# In[52]:


I = pd.read_pickle(dir+'RLInflows.pkl')['1971':]
O = pd.read_pickle(dir+'RR.pkl')['1971':]
H = pd.read_pickle(dir+'RL.pkl')['1971':]
A = 95700*10000/(24*3600)

plt.subplot(2,1,1)
I['1971'].plot()
plt.hold(True)
O['1971'].plot()
(A*H['1971'].diff()).plot()
(I['1971']-O['1971']).plot()
plt.hold(False)

plt.subplot(2,1,2)


Hp = (((I-O)).cumsum())/A
(Hp['1971']+H.ix[0]).plot()
plt.hold(True)
H['1971'].plot()
plt.hold(False)



# In[57]:


from mpl_toolkits.mplot3d import Axes3D

threedee = plt.figure().gca(projection='3d')

threedee.scatter(H['1971':'1999'],I['1971':'1999'],O['1971':'1999'])


# In[ ]: