In [1]:

    

from __future__ import absolute_import, division, print_function, unicode_literals

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib notebook


    

    




C:\Users\kevin.rose\AppData\Local\Continuum\Anaconda2\envs\py35\lib\site-packages\matplotlib\__init__.py:872: UserWarning: axes.color_cycle is deprecated and replaced with axes.prop_cycle; please use the latter.
  warnings.warn(self.msg_depr % (key, alt_key))

In [2]:

    

# The following code is adopted from Pat's Rolling Rain N-Year Threshold.pynb
# Loading in hourly rain data from CSV, parsing the timestamp, and adding it as an index so it's more useful

rain_df = pd.read_csv('data/ohare_full_precip_hourly.csv')
rain_df['datetime'] = pd.to_datetime(rain_df['datetime'])
rain_df = rain_df.set_index(pd.DatetimeIndex(rain_df['datetime']))
rain_df = rain_df['19700101':]
chi_rain_series = rain_df['HOURLYPrecip'].resample('1H').max()
print(rain_df.shape)


    

    




(468253, 5)

In [3]:

    

n_year_threshes = pd.read_csv('data/n_year_definitions.csv')
n_year_threshes = n_year_threshes.set_index('Duration')
n_year_threshes


    

    
Out[3]:






  

    

      

      
1-year
      
2-year
      
5-year
      
10-year
      
25-year
      
50-year
      
100-year
    
    

      
Duration
      

      

      

      

      

      

      

    
  
  

    

      
10-day
      
4.12
      
4.95
      
6.04
      
6.89
      
8.18
      
9.38
      
11.14
    
    

      
5-day
      
3.25
      
3.93
      
4.91
      
5.70
      
6.93
      
8.04
      
9.96
    
    

      
72-hr
      
2.93
      
3.55
      
4.44
      
5.18
      
6.32
      
7.41
      
8.78
    
    

      
48-hr
      
2.70
      
3.30
      
4.09
      
4.81
      
5.88
      
6.84
      
8.16
    
    

      
24-hr
      
2.51
      
3.04
      
3.80
      
4.47
      
5.51
      
6.46
      
7.58
    
    

      
18-hr
      
2.30
      
2.79
      
3.50
      
4.11
      
5.06
      
5.95
      
6.97
    
    

      
12-hr
      
2.18
      
2.64
      
3.31
      
3.89
      
4.79
      
5.62
      
6.59
    
    

      
6-hr
      
1.88
      
2.28
      
2.85
      
3.35
      
4.13
      
4.85
      
5.68
    
    

      
3-hr
      
1.60
      
1.94
      
2.43
      
2.86
      
3.53
      
4.14
      
4.85
    
    

      
2-hr
      
1.48
      
1.79
      
2.24
      
2.64
      
3.25
      
3.82
      
4.47
    
    

      
1-hr
      
1.18
      
1.43
      
1.79
      
2.10
      
2.59
      
3.04
      
3.56
    
    

      
30-min
      
0.93
      
1.12
      
1.41
      
1.65
      
2.04
      
2.39
      
2.80
    
    

      
15-min
      
0.68
      
0.82
      
1.03
      
1.21
      
1.49
      
1.75
      
2.05
    
    

      
10-min
      
0.55
      
0.67
      
0.84
      
0.98
      
1.21
      
1.42
      
1.67
    
    

      
5-min
      
0.30
      
0.36
      
0.46
      
0.54
      
0.66
      
0.78
      
0.91
    
  

In [4]:

    

n_year_threshes.loc['5-min', '1-year']


    

    
Out[4]:





0.29999999999999999

In [5]:

    

dur_str_to_hours = {
    '5-min':5/60.0,
    '10-min':10/60.0,
    '15-min':15/60.0,
    '30-min':0.5,
    '1-hr':1.0,
    '2-hr':2.0,
    '3-hr':3.0,
    '6-hr':6.0,
    '12-hr':12.0,
    '18-hr':18.0,
    '24-hr':24.0,
    '48-hr':48.0,
    '72-hr':72.0,
    '5-day':5*24.0,
    '10-day':10*24.0
}

def plot_thresh(duration_str, n_years, ax=None):
    '''
    TODO
    '''
    global rain_df
    global n_year_threshes
    
    if ax is None:
        plt.figure()
        ax = plt.gca()
    ax.hold(True)
    
    thresh = n_year_threshes.loc[duration_str, str(n_years) + '-year']
    
    duration = dur_str_to_hours[duration_str]
    duration = max(duration, 1) # cannot upsample to more frequent than hourly
    # TODO: want to throw warning?
    
    rain_line = chi_rain_series.rolling(window=int(duration), min_periods=0).sum().plot(ax=ax)
    
    x_limits = ax.get_xlim()
    
    thresh_line = ax.plot(x_limits, [thresh, thresh])
    
    ax.set_ylim([0, ax.get_ylim()[1]])
    
    ax.legend(['moving cumulative rain', str(n_years) + '-year ' + duration_str + ' threshold'],
              loc='best')


    

In [6]:

    

plot_thresh('48-hr', 100)


    

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