def map_plotter(longvals,latvals,meanvals,title,filename):
    plt.scatter(longvals,latvals, c=meanvals)
    plt.xlabel("Longitude")
    plt.ylabel("Latitude")
    plt.colorbar()
    plt.title(title)
    plt.savefig(filename)
    plt.show()

def october_anomoly(longvals,latvals,octvals,meanvals,title,filename):
    index = 0
    anomoly = []
    while index < len(longvals):
        anom = meanvals[index] - octvals[index]
        anomoly.append(anom)
        index = index + 1
    plt.scatter(longvals,latvals, c=anomoly)
    plt.xlabel("Longitude")
    plt.ylabel("Latitude")
    plt.colorbar()
    plt.title(title)
    plt.savefig(filename)
    plt.show()

def main():
    user_year = ask_year()
    if user_year < 2015 and user_year > 1899:
        print("Thank you for selecting the year", user_year)
        air_temp_data = read_data("data/air_temp_2014/air_temp." + str(user_year))
        precip_data = read_data("data/precip_2014/precip." + str(user_year))
        index = 0
        verify_climatology_data(air_temp_data,precip_data)
        menu_choice = get_menu_choice()
        if menu_choice == 1:
            #The following code creates the temperature line graph
            xs = get_month_names()
            is1 = get_located_between(air_temp_data,1,23.5,90)
            is2 = get_located_between(air_temp_data,1,-23.5,23.5)
            is3 = get_located_between(air_temp_data,1,-90,-23.5)
            index = 2
            ys = []
            ys2 = []
            ys3 = []
            while index < 14:
                month_val_N = statistics.mean(get_column_values(is1,index))
                month_val_C = statistics.mean(get_column_values(is2,index))
                month_val_S = statistics.mean(get_column_values(is3,index))
                ys.append(month_val_N)
                ys2.append(month_val_C)
                ys3.append(month_val_S)
                index += 1
            title = "Graph of global mean temperature values over 12 months in year " + str(user_year)
            y_axis = "Temperature in degrees Celcius"
            file_name = "global_mean_temp_" + str(user_year) + ".pdf"
            global_mean_plotter(xs,ys,ys2,ys3,y_axis,"Month",title,file_name)
            #This section of code creates the line graph of precip values
            is1 = get_located_between(precip_data,1,23.5,90)
            is2 = get_located_between(precip_data,1,-23.5,23.5)
            is3 = get_located_between(precip_data,1,-90,-23.5)
            index = 2
            ys = []
            ys2 = []
            ys3 = []
            while index < 14:
                month_val_N = statistics.mean(get_column_values(is1,index))
                month_val_C = statistics.mean(get_column_values(is2,index))
                month_val_S = statistics.mean(get_column_values(is3,index))
                ys.append(month_val_N)
                ys2.append(month_val_C)
                ys3.append(month_val_S)
                index += 1
            y_axis = "Precipitation"
            title = "Graph of global mean precipitation values over 12 months in year " + str(user_year)
            file_name = "global_mean_precip_" + str(user_year) + ".pdf"
            global_mean_plotter(xs,ys,ys2,ys3,y_axis,"Month",title,file_name)
        if menu_choice == 2:
            #The code below creates both the histogram for temperature and precip after
            #prompting the user for the amount of bins they would like.
            bin_count = int(input("How many bins would you like in your histograms?"))
            min_temp = get_column_values(air_temp_data, 14)
            min_precip = get_column_values(precip_data, 14)
            max_temp = get_column_values(air_temp_data, 15)
            max_precip = get_column_values(air_temp_data, 15)

            title_temp = "Histogram of max/min global temperature in " + str(user_year)
            title_precip = "Histogram of max/min global precipitation in " + str(user_year)

            ylabel = "Number of locations"
            xlabel_temp = "Temperature"
            xlabel_precip = "Precipitation"
            file_name_temp = "histogram_temperature_" + str(user_year) + ".pdf"
            file_name_precip = "histogram_precip_" + str(user_year) + ".pdf"

            global_histogram(bin_count,min_temp,max_temp, ylabel, xlabel_temp, title_temp, file_name_temp)
            global_histogram(bin_count, min_precip,max_precip, ylabel, xlabel_precip, title_precip, file_name_precip)
        if menu_choice == 3:
            print("Run option 3")
        if menu_choice == 4:
            longvals = get_column_values(air_temp_data, 0)
            latvals = get_column_values(air_temp_data, 1)
            meanvals = get_column_values(air_temp_data, 16)
            title = "Heat map of temperature values in year " + str(user_year)
            filename = "heat_map_temp_" + str(user_year) + ".pdf"
            map_plotter(longvals,latvals,meanvals,title,filename)
            #precipitation
            longvalsp = get_column_values(precip_data, 0)
            latvalsp = get_column_values(precip_data, 1)
            sumvalsp = get_column_values(precip_data, 17)
            title = "Heat map of precipitation values in year " + str(user_year)
            filename = "heat_map_precip_" + str(user_year) + ".pdf"
            map_plotter(longvalsp,latvalsp,sumvalsp,title,filename)
        if menu_choice == 5:
            #This function will find the temperature and precipitation anomoly in October and create a heatmap.
            #This type of map is used quite a bit in climatology.
            longvals = get_column_values(air_temp_data, 0)
            latvals = get_column_values(air_temp_data, 1)
            octtemp = get_column_values(air_temp_data, 11)
            meanvals = get_column_values(air_temp_data, 16)
            title = "Temperature anomoly in October " + str(user_year)
            filename = "oct_anom_temp_" + str(user_year) + ".pdf"
            october_anomoly(longvals,latvals,octtemp,meanvals,title,filename)
            #precipitation
            longvalsp = get_column_values(precip_data, 0)
            latvalsp = get_column_values(precip_data, 1)
            octprecip = get_column_values(precip_data, 11)
            meanvalsp = get_column_values(precip_data, 16)
            title = "Precipitation anomoly in October " + str(user_year)
            filename = "oct_anom_temp_" + str(user_year) + ".pdf"
            october_anomoly(longvalsp,latvalsp,octprecip,meanvals,title,filename)
        if menu_choice == 6:
            print("Pie Chart of Precip as compared to mean")
        if menu_choice == 0:
            return
    else:
        print("Try again next time!")
        return

if __name__ == "__main__":
    main()