'''
Created on Apr 10, 2014
@author: Brett Paufler
Copyright Brett Paufler



TAKES RAW CORN DATA AND PROVIDES GRAPH BASED UPON INPUT VALUE YEARS


Time Spent  3-4 hours at first run
'''


#import BS
import pandas

import matplotlib.pyplot as plt



def monthDayNumberArray():
    '''Returns a default Month Day array for use as a key
        01-01 to 12-31, including 02-29, 02-30, 02-31 and so on    
    '''
    dates = []
    for m in range(1,13,1):
        if m < 10:
            m = "0" + str(m)
        for d in range(1,32,1):
            if d < 10:
                d = "0" + str(d)
            date = str(m) + "-" + str(d)
            #print date
            dates.append(date)
    return dates
    #print dates


def numberToMonth(x):
    '''x is a month-date string
    01-01 returns 'January 01
    '''
    if x.startswith('01-'):
        x = "January "  + x[3:]
    elif x.startswith('02-'):
        x = "February "  + x[3:]
    elif x.startswith('03-'):
        x = "March "  + x[3:]
    elif x.startswith('04-'):
        x = "April "  + x[3:]
    elif x.startswith('05-'):
        x = "May "  + x[3:]
    elif x.startswith('06-'):
        x = "June "  + x[3:]
    elif x.startswith('07-'):
        x = "July "  + x[3:]
    elif x.startswith('08-'):
        x = "August "  + x[3:]
    elif x.startswith('09-'):
        x = "September "  + x[3:]
    elif x.startswith('10-'):
        x = "October "  + x[3:]
    elif x.startswith('11-'):
        x = "November "  + x[3:]
    elif x.startswith('12-'):
        x = "December "  + x[3:]       
    
    
    
    
    return x
    


def dailyPriceOfIssue(years=["2012", "2013"], full=True):
    '''Returns a dataFrame:
        MD = 01-01, 12-31 date index
        CZXXXX_High = high price per day of selected CZ issues
    
    years takes an array object of year data desired (not a range, but a list)
        drawn automatically from rawPath = "./corn/"
    
    default full=True, means all dates are used, even NaN and garbage values
    False filters out NaN for prettier graphs, but at longer year runs, data is meaningless
    '''
    print "dailyPriceStackedGraphByYears called"
    
    #assembles the files to call, the paths to the data
    rawPath = "./corn/"
    
    #create month & day index

    dates = monthDayNumberArray()
    
    dF = pandas.DataFrame(dates, index=dates, columns=["MD"])
    
    #cycles through the issues
    for year in years:
        
        #makes the file path
        dP = rawPath + "FUTURE_CZ" + year + ".csv"

        #This is the straight import
        #sIA = pandas.read_csv(dP, index_col='Date', parse_dates=['Date'])
        sIA = pandas.read_csv(dP)

        #yB = yearBegin, yE = yearEnd
        yB = str(str(year) + "-01-01")
        yE = str(str(year) + "-12-31")
        
        #slices issue down to year yB, yE
        #and makes sure High isn't zero
        sIA = sIA[sIA.Date >= yB]
        sIA = sIA[sIA.Date <= yE]
        sIA = sIA[sIA.High >= 25] # a little more aggressive than zero
        
        
        #slices the year down to a month day
        sIA["MD"] = sIA.Date.map(lambda Date: Date[5:])

        #Removes unwanted variables
        #So This is where they would be added back in
        del sIA["Date"]
        del sIA["Open Interest"]
        del sIA["Open"]
        del sIA["Low"]
        del sIA["Settle"]
        del sIA["Volume"]
        
        #renaming High
        sIA["CZ" + year + " High"] = sIA["High"]
        del sIA["High"]
                
        print sIA
        print "sIA printed"
        
        #merges the base MD (01-31) array with the current array
        if full:
            dF = pandas.merge(dF, sIA, how='left', left_index=True, right_on=['MD'])
        else:
            dF = pandas.merge(dF, sIA, left_index=True, right_on=['MD'])
        
        #kills unwanted columns
        #Cheesy, sure, but throws an error occanssionally
        
        try:
            del dF['MD_x']
        except:
            pass
        try:
            del dF['MD_y']
        except:
            pass
              
        dF = dF.set_index("MD") 
        print dF
    
    print dF
    print "dailyPriceStackedGraphByYears Ended returned dF"
    return dF
#END dailyPriceStackedGraphByYears
#dailyPriceOfIssue()

def prettyPrintMonth(dF):
    ''' takes a dataFrame with 01-01 to 12-31 format and returns one with pretty print
    January to December format
    '''
    dF['MonthDate'] = dF.index.map(lambda index: numberToMonth(index))
    dF = dF.set_index("MonthDate")
    print dF
    print 'prettyPrintMonth worked'
    return dF
#prettyPrintMonth(dailyPriceOfIssue())


def graphAlot(toPlot, name):
    '''
    Fast graphing output for various inputs
    toPlot is a pandas dataFrame
    name could be whatever, but CZ2000-CZ2014 range will workBest
    '''
    #standardizes the size
    plt.rcParams['figure.figsize'] = 20,10
    print "graphAlot called"
    
    fig = toPlot.boxplot()
    outputName = "./chartsOut/" + name + "_BoxPlot.png"
    print "Working On " + outputName
    plt.savefig(outputName)
    
    fig = toPlot.plot()
    outputName = "./chartsOut/" + name + "_Line.png"
    print "Working On " + outputName
    plt.savefig(outputName)

    fig = toPlot.plot(kind="bar")
    outputName = "./chartsOut/" + name + "_Bar.png"
    print "Working On " + outputName
    plt.savefig(outputName)

    print "graphBox Done output in Charts"
    print "Base Name is " + name

def graphBox(toPlot, name):
    '''Just the boxPlot graph
    
    
    '''

    
    print "graphBox Done output in Charts"
    print "Base Name is " + name


years= []
for x in range(2000, 2014,1):
    years.append(str(x)) 
print years



#graphAlot(prettyPrintMonth(dailyPriceOfIssue(years)), "CZ2000-TO-CZ2013_ALL")
#graphAlot(prettyPrintMonth(dailyPriceOfIssue(["2010", "2011", "2012", "2013"])), "CZ2010-TO-CZ2013_ALL")
#graphAlot(prettyPrintMonth(dailyPriceOfIssue(["2010", "2011", "2012", "2013"], full=False)), "CZ2010-TO-CZ2013_Partial")
#graphAlot(prettyPrintMonth(dailyPriceOfIssue(["2012", "2013"])), "CZ2012-TO-CZ2013_ALL")        
#graphAlot(prettyPrintMonth(dailyPriceOfIssue(["2012", "2013"], full=False)), "CZ2012-TO-CZ2013_Partial")



#dailyPriceOfIssue(years)
#plt.show()
#plt.bar(years,low, color='yellow')

print "DONE WITH EVERYTHING"