storify.py

# Accepts a results dictionary and writes an short analysis based on
# the stored results.  Example:

# test_res_dict = {
#     'address' : '1460 Golden Gate Avenue, San Francisco, CA',
#     'sold_date' : '2008-04-21',

#     # baseline level of vegetation or some other sort of indicator of
#     # the property.
#     'pre_ndvi'  : 100,
    
#     # value at maximal change and test statistic after the selling
#     # date
#     'post_ndvi' : 50,
#     'diff_statistic' : 2.1,

#     # The date that the empirical fluctuation process exceeded the
#     # confidence threshold
#     'stats_date' : '2009-05-12'  
# }

# >>> story(test_res_dict)
# 'The property at 1460 Golden Gate Avenue, San Francisco, CA was last
# sold on Tuesday, May 12, 2009. The property was subject to
# redevelopment after it was sold. Approximately 386 days after the
# property was sold, 50 percent of the land underwent significant
# development'


from datetime import datetime


def _intro(res_dict):
    d = datetime.strptime(res_dict['stats_date'], '%Y-%m-%d')
    date = d.strftime("%A, %B %d, %Y")
    text = ('The property at %s' % res_dict['address'], 
            'was last sold on %s.' % date)
    return [' '.join(text)]


def _analysis(res_dict):
    """If there is analysis to do"""
    sold = datetime.strptime(res_dict['sold_date'], '%Y-%m-%d')
    stat = datetime.strptime(res_dict['stats_date'], '%Y-%m-%d')
    days = (stat-sold).days

    p = int(float(res_dict['post_ndvi']) / res_dict['pre_ndvi'] * 100)

    s1 = ['The property was subject to redevelopment after it was sold.']
    s2 = ['Approximately %s days after the property was sold,' % days,
          '%s percent of the land underwent significant development' % p]

    return [' '.join(s1 + s2)]
    

def story(res_dict):
    s1 = _intro(res_dict)
    if abs(res_dict['diff_statistic']) > 1.96:
        s2 = _analysis(res_dict)
    else:
        s2 = ['There was no significant redevelopment of ' +  
              'the property after it was sold']
    return ' '.join(s1 + s2)