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show_domains.py
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show_domains.py
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import sys
import numpy as np
import matplotlib.colors as pltcol
from matplotlib import cm
from matplotlib.colors import colorConverter, Normalize, SymLogNorm, cnames
from matplotlib.pyplot import *
import random
from util import clip_and_blur, read_domains, clip, topify, remove_empty_domains, interpolated
from util import for_each_diagonal, smooth, matrix_from_list, heatmap, heatmap_notlog
from find_domains import z_score_matrix
from util import domains_affinity, inter_domain_contacts
from util import read_cc, fix_ticks, flip_to_diagonal
from clustering import k_medoids
from IPython.core.debugger import Tracer
from scipy.optimize import curve_fit
import scipy.cluster
BORDER_COLOR = 'WHITE'
COLORS = {
'0': 'WHITE',
'A': 'BLACK',
'B': 'RED',
'C': 'GREEN',
'D': 'PURPLE',
'E': 'BROWN',
'F': 'TURQUOISE'
}
COLOR_LIST = random.sample(cnames, 100)
#print COLOR_LIST
DOM_THR = 0
def colored_with_affinity(arr, domains, affinity=False, chr=None, cc=None):
arr = np.ma.fix_invalid(arr)
# PuBu
colored = cm.jet(pltcol.LogNorm()(arr))
normalizer = Normalize(vmin=-1, vmax=3)
non_empty_domains = remove_empty_domains(arr, topify(domains))
if affinity:
doms_affinity = domains_affinity(arr, non_empty_domains)
heatmap_notlog(np.clip(doms_affinity, 0, 10))
doms_affinity_log = np.log(doms_affinity)
affinity_thr = np.nanmean(doms_affinity_log) + np.nanstd(doms_affinity_log)
affinity_thr = np.exp(affinity_thr)
affinity_thr = np.nanmean(doms_affinity) + 1 * np.nanstd(doms_affinity)
affinity_normalizer = Normalize(vmin=affinity_thr, vmax=10)
for i, dom in enumerate(domains):
begin, end = dom.get_begin(), dom.get_end()
if end - begin < DOM_THR:
continue
color = dom.color or BORDER_COLOR
try:
color_num = int(dom.color)
if color_num >=0 :
color = COLOR_LIST[color_num]
else:
color = COLORS['0']
except:
pass
if cc:
color = COLORS[cc.get((chr, dom.color), '0')]
color = colorConverter.to_rgba(color)
for i in range(begin, end + 1):
if i != end:
colored[i, end] = color
if i != begin:
colored[begin, i] = color
#colored[begin, begin] = colorConverter.to_rgba('black')
#colored[end, end] = colorConverter.to_rgba('black')
if affinity:
for i, dom in enumerate(non_empty_domains):
begin, end = dom.get_begin(), dom.get_end()
for j, dom2 in enumerate(non_empty_domains):
if j <= i:
continue
begin2, end2 = dom2.get_begin(), dom2.get_end()
if doms_affinity[i, j] < affinity_thr:
continue
color = cm.gnuplot(affinity_normalizer(doms_affinity[i, j]))
for k in range(begin, end + 1):
colored[k, begin2] = color
colored[k, end2] = color
for k in range(begin2, end2 + 1):
colored[begin, k] = color
colored[end, k] = color
return colored
if __name__ == '__main__':
if len(sys.argv) < 3:
print '[-cc cc_file1 [-cc2 cc_file2]] arr domains (arr2 domains2)'
cc1 = None
cc2 = None
if sys.argv[1] == '-cc':
cc1 = read_cc(open(sys.argv[2], 'r'))
sys.argv = sys.argv[2:]
if sys.argv[1] == '-cc2':
cc2 = read_cc(open(sys.argv[2], 'r'))
sys.argv = sys.argv[2:]
blur = True
comparing = len(sys.argv) > 3
colorize = False
show_affinity = True
arr = np.load(sys.argv[1])
chr1 = sys.argv[1].split('/')[-1].split('.')[0].split('_')[0]
if blur:
arr = clip_and_blur(arr)
else:
arr = clip(arr)
if comparing:
arr = np.triu(arr)
doms = read_domains(open(sys.argv[2], 'r'))
result = colored_with_affinity(arr, doms, chr=chr1, cc=cc1)
if comparing:
arr2 = np.load(sys.argv[3])
chr2 = sys.argv[3].split('/')[-1].split('.')[0].split('_')[0]
doms2 = read_domains(open(sys.argv[4], 'r'))
if blur:
arr2 = clip_and_blur(arr2)
else:
arr2 = clip(arr2)
arr2 = np.triu(arr2, 1)
result2 = colored_with_affinity(arr2, doms2, chr=chr2, cc=cc2)
result += np.transpose(result2, (1, 0, 2))
else:
result = flip_to_diagonal(result)
figure(figsize=(8,8))
imshow(result, origin='lower', interpolation='nearest')
fix_ticks()
title(sys.argv[-1])
show()
#savefig(sys.argv[-1]+".pdf",dpi=1200)