def get_blue_matrix_df(self):
h_data = historical_data()
rs = h_data.get_all_data()
return DataFrame(census_data.get_blue_matrix(rs))
if debug==1:print (row['length'].values[0])
temp_rs = analyze_blue.calc_probability(df3,row['max'].values[0].astype(int),row['length'].values[0])
if i==1:
rs=temp_rs
else :
rs=np.concatenate((rs, temp_rs))
previous_line=end_line
return rs
if __name__ == '__main__':
import dblottery
from query_historical_data import historical_data
from census import census_data
db = dblottery.dblottery()
historical_data=historical_data()
rs=historical_data.get_all_data()
blue_matrix_frame = DataFrame(census_data.get_blue_matrix(rs))
df= blue_matrix_frame.loc[:,[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16]].cumsum()
df[17]=blue_matrix_frame[0]
df['index']=df.index
df.to_csv('summaryBlue.csv',index=False)
dfCensusResult= analyze_blue.get_blue_census(df)
#print dfCensusResult
rs = analyze_blue.get_probability_matrix(blue_matrix_frame,dfCensusResult)
rs_df=DataFrame(rs)
rs_df['IDENTIFIER']=df[17]
#print rs_df
#rs_df.to_csv('CensusBlue.csv',index=False)