long_inter/differences_interdomain.py at master · irinatu/long_inter · GitHub

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from sys import argv, exit
from collections import defaultdict

import optparse, os, math
import numpy as np
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from matplotlib.colors import LogNorm

from util import clip_and_blur

from matplotlib.backends import backend_pdf
from matplotlib import rcParams, cm


def lines(path,header=True):
    with open(path,'r') as handle:
        if header:
            handle.next()
        else: pass
        for line in handle:
            yield line.split('\n')[0].split(' ')

def parse_domains(gen):
    domains = defaultdict(list)
    end0 = 0.0
    for l in gen:
        #print l
        if l[1] == opts.Level and l[2] == opts.Chrom:
            start = float(l[3])/150000.0
            end = (float(l[4].split("\n")[0])/150000.0) - 1
            lev = l[1]
            if end > end0: end0 = end
            domains[("lev"+lev, l[0])].append((start,end))
    return domains, end0, lev

def plot_all(mtx, mt_i, xy, out):
    #with backend_pdf.PdfPages("%s_roznicowa_Rafala.pdf" % ( os.path.basename(out))) as pdf:
        #plt.figure(dpi=1200)
        #mtx = np.load(mat)
        #fig = plt.figure(dpi=2200)
        #fig = plt.figure()
        #colormap = plt.cm.gist_ncar
        #plt.imshow(mtx,interpolation='nearest',origin='lower',norm=LogNorm(),cmap=cm.jet)

    #plt.imshow(np.tril(mtx),origin='lower',norm=LogNorm(),cmap="Blues", interpolation='nearest')
    x,y = zip(*xy)
    plt.plot(x,y,linestyle='-',linewidth=0.3, color = 'black')

    plt.imshow(mt_i, norm=LogNorm(), cmap="Reds",interpolation='none', origin = 'upper')
    plt.colorbar()
    plt.imshow(np.tril(mtx),norm=LogNorm(), cmap="Blues", interpolation='nearest', origin = 'upper')
    #plt.show()

    #ax=pylab.gca()
    #ax.set_ylim(ax.get_ylim()[::-1])

    #plt.axis([0,mtx.shape[0],0,mtx.shape[0]])
    plt.legend(loc='best')
    plt.title("Plot",fontsize=7)
    out = "%s_diff_Rafala.png" % ( os.path.basename(out).split('.')[0])
    plt.savefig(out, dpi = 1500, bbox_inches='tight')
    plt.show()
    plt.close()
    print "finished plotting"

def prepar_interac_matr(inte, si, dom):
    i_m = np.zeros((si, si))
    ZERO = True
    #print dom
    header = True
    if header: inte.next()
    else: pass
    int_dict = {}
    for l in inte:
        #print l
        if l[2] != '0.0' and float(l[2]) < 0.05:
            print "NIE 0.0"
            dom1 = [dom[i] for i in dom.keys() if i[1] == l[0]]
            dom2 = [dom[i] for i in dom.keys() if i[1] == l[1]]
            dom1_2 = sum(dom1 + dom2,[])
            #print dom1_2
            if dom1_2[0]==dom1_2[1]:
                #print dom1_2[0], dom1_2[1]
                i_m[int(dom1_2[0][0]):int(dom1_2[0][1])+1, int(dom1_2[1][0]):int(dom1_2[1][1])+1] = 0.0

            elif len(dom1_2) == 2:
                #print dom1_2[0][0], int(dom1_2[0][1])+1, dom1_2[1][0], int(dom1_2[1][1])+1, i_m.shape
                #i_m[int(dom1_2[0][0]):int(dom1_2[0][1])+1, int(dom1_2[1][0]):int(dom1_2[1][1])+1] = round(-math.log10(float(l[2])), 5)
                i_m[int(dom1_2[0][0]):int(dom1_2[0][1])+1, int(dom1_2[1][0]):int(dom1_2[1][1])+1] = 1.0
                domeny = "%s %s" %(l[0], l[1])
                int_dict[domeny]=l[2]

            elif len(dom1_2) == 1:
                #print dom1_2, dom1, dom2
                i_m[int(dom1_2[0][0]):int(dom1_2[0][1])+1, int(dom1_2[1][0]):int(dom1_2[1][1])+1] = 1.0
                domeny = "%s %s" %(l[0], l[1])
                int_dict[domeny]=l[2]

            else: print "More domains!!!!", dom1_2
        elif l[2] == '0.0' and ZERO:

            dom1 = [dom[i] for i in dom.keys() if i[1] == l[0]]
            dom2 = [dom[i] for i in dom.keys() if i[1] == l[1]]
            dom1_2 = sum(dom1 + dom2,[])

            if dom1_2[0]==dom1_2[1]:
                #print dom1_2[0], dom1_2[1]
                i_m[int(dom1_2[0][0]):int(dom1_2[0][1])+1, int(dom1_2[1][0]):int(dom1_2[1][1])+1] = 0.0

            elif len(dom1_2) == 2:
                #print dom1_2, type(dom1)
                #i_m[int(dom1_2[0][0]):int(dom1_2[0][1])+1, int(dom1_2[1][0]):int(dom1_2[1][1])+1] = 500
                i_m[int(dom1_2[0][0]):int(dom1_2[0][1])+1, int(dom1_2[1][0]):int(dom1_2[1][1])+1] = 1.0
                domeny = "%s %s" %(l[0], l[1])
                int_dict[domeny]=l[2]

            elif len(dom1_2) == 1:
                #print dom1_2, dom1, dom2
                i_m[int(dom1_2[0][0]):int(dom1_2[0][1])+1, int(dom1_2[1][0]):int(dom1_2[1][1])+1] = 1.0
                domeny = "%s %s" %(l[0], l[1])
                int_dict[domeny]=l[2]

            else: print "More domains!!!!", dom1_2
        else:
            pass

    return np.triu(i_m), int_dict

if __name__=="__main__":

    optparser = optparse.OptionParser(usage = "%prog [<options>]")
    optparser.add_option('-m', type = "string", default = "", dest="Matrix", help = "Numpy matrix in npy format")
    optparser.add_option('-d', type = "string", default = "", dest="Domains", help ="Txt file with domain information")
    optparser.add_option('-i', type = "string", default = "", dest="Interaction", help ="Txt file with domain-domain interactions")
    optparser.add_option('-f', type = "string", default = "", dest="Files", help ="Txt file with information abouth the whole path of domin and interactions files in the collumns in the format domain_path interaction_path ")
    optparser.add_option('-l', type = "string", default = "", dest="Level", help ="The level of sherpa")
    optparser.add_option('-c', type = "string", default = "", dest="Chrom", help ="The level of sherpa")

    (opts,args) = optparser.parse_args()
    if len(argv) ==1:
        print optparser.format_help()
        exit(1)

    domeny, dl, level = parse_domains(lines(opts.Domains, header=False))
    #print domeny

    inter_mtx, interac_d = prepar_interac_matr(lines(opts.Interaction, header=False), dl, domeny)

    matr = np.load(opts.Matrix)

    matr = clip_and_blur(matr)

    other_mtx=lines(opts.Files, header=True)
    int_mtres = []
    for lin in other_mtx:
        dom, d, level = parse_domains(lines(lin[0], header=False))
        int_m, dict = prepar_interac_matr(lines(lin[1], header=False), d, dom)
        int_mtres.append(int_m)

    #plt.imshow(inter_mtx,origin='lower',norm=LogNorm(),cmap="Reds")
    #plt.show()
    #plt.imshow(int_mtres[0],origin='lower',norm=LogNorm(),cmap="Reds")
    #plt.show()

    for ma in int_mtres:
        inter_mtx[np.where(inter_mtx==ma)] = 0.0

    xyki = []
    for d_key in domeny.keys():
        xyki = xyki + sum([[(start,start), (end,start), (end,end)] for start, end in domeny[d_key]],[])

    new = np.zeros_like(inter_mtx)
    #print np.sum(new)

    for key in interac_d.keys():
        #print key, domeny
        ke = ('lev'+level, key.split(' ')[0])
        ka = ('lev'+level, key.split(' ')[1])
        if np.sum(inter_mtx[int(domeny[ke][0][0]):int(domeny[ke][0][1])+1, int(domeny[ka][0][0]):int(domeny[ka][0][1])+1]) != 0.0:
            if float(interac_d[key]) != 0.0:
                new[int(domeny[ke][0][0]):int(domeny[ke][0][1])+1, int(domeny[ka][0][0]):int(domeny[ka][0][1])+1][np.where(inter_mtx[int(domeny[ke][0][0]):int(domeny[ke][0][1])+1, int(domeny[ka][0][0]):int(domeny[ka][0][1])+1] == 1.0)] = round(-math.log10(float(interac_d[key])), 5)
            else:
                print "p-val = 0!!!"
                new[int(domeny[ke][0][0]):int(domeny[ke][0][1])+1, int(domeny[ka][0][0]):int(domeny[ka][0][1])+1][np.where(inter_mtx[int(domeny[ke][0][0]):int(domeny[ke][0][1])+1, int(domeny[ka][0][0]):int(domeny[ka][0][1])+1] == 1.0)] = 500.0
            print ke[1], ka[1], interac_d[key]

    plot_all(matr, new, xyki, opts.Interaction)


    #Sprawdzenie symetrycznosci
    #inter_mtx[np.isnan(inter_mtx)] = 0
    #print  np.allclose(np.transpose(inter_mtx), inter_mtx), inter_mtx.size - np.isnan(inter_mtx).sum()