int vs int plot

gistfile1.txt

import numpy as np
import matplotlib.pyplot as plt

def bucket_int_comp(labels, data, bucketsize, perc):
    count= 0
    for dat in data:
        float_data= []
        f_data= []
        b_data= []
        b_labels= []
        running= True
        i=1
        sum=0
        for num in dat:
            float_data.append(float(num))
        perc_value= np.percentile(float_data, perc)
        for num in float_data:
            if num<= perc_value:
                f_data.append(0.0)
            else:
                f_data.append(num-perc_value)
        while running:
            if i+bucketsize>=len(dat):
                running=False
                
            else:
                for num in f_data[i:(i+bucketsize)]:
                    sum+=float(num)
                    
                b_data.append(sum)
                b_labels.append((float(labels[i+bucketsize/2])))

                if i+bucketsize<len(dat):
                    i+=bucketsize
                    sum=0
                    
                else:
                    running= False
        if count == 0:
            Ecoli1= b_data
            Ecoli1_labels= b_labels
        elif count == 1:
            Ecoli2= b_data
            Ecoli2_labels= b_labels
        else:
            Kpneumoniae= b_data
            Kpneumoniae_labels= b_labels
        count+=1
    r_Ecoli1= []
    r_Ecoli2= []
    r_Kpneumoniae= []
    max_Ecoli1= max(Ecoli1)
    max_Ecoli1_labels= max(Ecoli1_labels)
    for num in Ecoli1:
        r_Ecoli1.append(num*max_Ecoli1_labels/max_Ecoli1)
    for num in Ecoli2:
        r_Ecoli2.append(num*max_Ecoli1_labels/max_Ecoli1)
    for num in Kpneumoniae:
        r_Kpneumoniae.append(num*max_Ecoli1_labels/max_Ecoli1)
    
    
    NPOINTS = len(Kpneumoniae)
    RESFACT=10
    MAP='rainbow'

    fig = plt.figure()

    ax1= fig.add_subplot(2,2,1)
    cm = plt.get_cmap(MAP)
    ax1.set_color_cycle([cm(1.*i/(NPOINTS-1)) for i in range(NPOINTS-1)])
    for i in range(NPOINTS-1):
        ax1.plot(Kpneumoniae[i:i+2],Ecoli1[i:i+2], marker= ".", ls=" ")
    #plt.plot(Kpneumoniae,Ecoli1)
    plt.xlabel("K. pneumoniae - 164092")
    plt.ylabel("E. coli - 163906")

    ax2= fig.add_subplot(2,2,2)
    cm = plt.get_cmap(MAP)
    ax2.set_color_cycle([cm(1.*i/(NPOINTS-1)) for i in range(NPOINTS-1)])
    for i in range(NPOINTS-1):
        ax2.plot(Kpneumoniae[i:i+2],Ecoli2[i:i+2], marker= ".", ls=" ")
    #plt.plot(Kpneumoniae,Ecoli2)
    plt.xlabel("K. pneumoniae - 164092")
    plt.ylabel("E. coli - 163962")

    ax3= fig.add_subplot(2,2,3)
    cm = plt.get_cmap(MAP)
    ax3.set_color_cycle([cm(1.*i/(NPOINTS-1)) for i in range(NPOINTS-1)])
    for i in range(NPOINTS-1):
        ax3.plot(Ecoli1[i:i+2],Ecoli2[i:i+2], marker= ".", ls=" ")
    #plt.plot(Ecoli1,Ecoli2)
    plt.xlabel("E. coli - 163906")
    plt.ylabel("E. coli - 163962")

    ax4= fig.add_subplot(2,2,4)
    cm = plt.get_cmap(MAP)
    ax4.set_color_cycle([cm(1.*i/(NPOINTS-1)) for i in range(NPOINTS-1)])
    for i in range(NPOINTS-1):
        ax4.plot(Ecoli1[i:i+2],Ecoli1[i:i+2], marker= ".", ls=" ")
    #plt.plot(Ecoli1,Ecoli1)
    plt.xlabel("E. coli - 163906")
    plt.ylabel("E. coli - 163906")

    plt.show()