PanGenomeDataPlot.py

# -*- coding: utf-8 -*-
import matplotlib
matplotlib.use("Agg")
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
from scipy.interpolate import spline
import argparse
import sys

def options( ):
    parser = argparse.ArgumentParser(description="Generates Line plots with shaded area for the data generated by Pangenome tool",formatter_class=argparse.ArgumentDefaultsHel
pFormatter)
    parser.add_argument("--rtab",dest="rtab",help="Input Rtab file",type=file)
    parser.add_argument("--figname",dest="figname",help="Output figure file name",type=str,default="PrettyFig")
    parser.add_argument("--title",dest="title",help="title of the figure",type=str,default="")
    parser.add_argument("--width",dest="width",help="width of figure in inch",type=int,default=16)
    parser.add_argument("--height",dest="height",help="height of figure in inch",type=int,default=9)
    parser.add_argument("--dpi",dest="dpi",help="DPI",type=int,default=300)
    parser.add_argument("--xlabel",dest="xlabel",help="X axis label",type=str,default="")
    parser.add_argument("--ylabel",dest="ylabel",help="Y axis label",type=str,default="")
    parser.add_argument("--font",dest="font",help="Font type",type=str,default="normal")
    parser.add_argument("--fsize",dest="fsize",help="Font size",type=int,default=12)
    parser.add_argument("--figformat",dest="figformat",type=str,default="png")
    return parser.parse_args( )

def fig_plot(inputs):
    font = {'family' : inputs["font"],
            'weight' : 'bold',
            'size'   : inputs["fsize"]}
    plt.rc(font)
    plt.figure(figsize=(inputs["width"],inputs["height"]),dpi=inputs["dpi"])
    data2 = pd.read_csv(inputs["rtab"],sep="\t",header=None)
    bx = []
    means = []
    medians = []
    lower_quartilles = []
    upper_quartilles = []
    lower_whiskers = []
    upper_whiskers = []
    for j in data2.columns.tolist():
        tdt = np.array(data2[j])
        median = np.median(tdt)
        medians.append(median)
        mean= np.mean(tdt)
        means.append(mean)
        lower_quartille = np.percentile(tdt,25)
        lower_quartilles.append(lower_quartille)
        upper_quartille = np.percentile(tdt,75)
        upper_quartilles.append(upper_quartille)
        iqr = upper_quartille-lower_quartille
        lower_whisker = tdt[tdt>=lower_quartille-1.5*iqr].min()
        lower_whiskers.append(lower_whisker)
        upper_whisker = tdt[tdt<=upper_quartille+1.5*iqr].max()
        upper_whiskers.append(upper_whisker)
    x = np.arange(1,len(upper_whiskers)+1)
    xl = np.linspace(x.min(),x.max(),len(x))
    smooth = 1
    if smooth:
        medians = spline(x,medians,xl)
        means = spline(x,means,xl)
        upper_quartilles = spline(x,upper_quartilles,xl)
        lower_quartilles = spline(x,lower_quartilles,xl)
        upper_whiskers = spline(x,upper_whiskers,xl)
        lower_whiskers = spline(x,lower_whiskers,xl)
    plt.figure(figsize=(inputs["width"],inputs["height"]),dpi=inputs["dpi"])
    plt.fill_between(xl,np.array(lower_whiskers),np.array(upper_whiskers),facecolor="orange",alpha=0.3,lw=0)
    plt.fill_between(xl,np.array(lower_quartilles),np.array(upper_quartilles),facecolor="orange",alpha=0.3,lw=0)
    plt.plot(xl,means,c='orange',alpha=1)
    plt.plot(xl,medians,c='blue',alpha=1)
    plt.xlabel(inputs["xlabel"])
    plt.ylabel(inputs["ylabel"])
    plt.title(inputs["title"])
    plt.savefig("%s.%s"%(inputs["figname"],inputs["figformat"]),bbox_inches="tight")

if __name__=='__main__':
    args = options( )
    inputs = {
                "rtab":args.rtab,
                'figname':args.figname,
                'title':args.title,
                'width':args.width,
                'height':args.height,
                'dpi':args.dpi,
                'xlabel':args.xlabel,
                'ylabel':args.ylabel,
                'font':args.font,
                'fsize':args.fsize,
                "figformat":args.figformat
            }
    fig_plot(inputs)