def test_06_tad_clustering(self):
if ONLY and ONLY != '06':
return
if CHKTIME:
t0 = time()
test_chr = Chromosome(name='Test Chromosome',
experiment_tads=[exp4],
experiment_names=['exp1'],
experiment_hic_data=[
PATH + '/20Kb/chrT/chrT_D.tsv'],
experiment_resolutions=[20000,20000],
silent=True)
all_tads = []
for _, tad in test_chr.iter_tads('exp1', normed=False):
all_tads.append(tad)
#align1, align2, _ = optimal_cmo(all_tads[7], all_tads[10], 7,
# method='score')
align1, align2, _ = optimal_cmo(all_tads[1], all_tads[3], 7,
method='score')
# Values with square root normalization.
#self.assertEqual(align1, [0, 1, '-', 2, 3, '-', 4, 5, 6, 7, 8, 9, 10])
#self.assertEqual(align2,[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12])
self.assertEqual(align1, [0, 1, 2, '-', '-', 3, 4, 5, 6, 7, 8, '-', 9])
self.assertEqual(align2, [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12])
if CHKTIME:
print '6', time() - t0
def test_06_tad_clustering(self):
if ONLY and not "06" in ONLY:
return
if CHKTIME:
t0 = time()
test_chr = Chromosome(
name="Test Chromosome",
experiment_tads=[exp4],
experiment_names=["exp1"],
experiment_hic_data=[PATH + "/20Kb/chrT/chrT_D.tsv"],
experiment_resolutions=[20000, 20000],
silent=True)
all_tads = []
for _, tad in test_chr.iter_tads("exp1", normed=False):
all_tads.append(tad)
#align1, align2, _ = optimal_cmo(all_tads[7], all_tads[10], 7,
# method="score")
align1, align2, _ = optimal_cmo(all_tads[1],
all_tads[3],
7,
method="score")
# Values with square root normalization.
#self.assertEqual(align1, [0, 1, "-", 2, 3, "-", 4, 5, 6, 7, 8, 9, 10])
#self.assertEqual(align2,[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12])
self.assertEqual(align1, [0, 1, 2, "-", "-", 3, 4, 5, 6, 7, 8, "-", 9])
self.assertEqual(align2, [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12])
if CHKTIME:
print "6", time() - t0
def main():
"""
main function
"""
tad1, tad2, contacts1, contacts2 = generate_random_contacts(size=12,
prob_mut=0.5,
num_changes=2)
size1 = len(tad1)
size2 = len(tad2) #max([max(c) for c in contacts2])
num_v = min(size1, size2)
#align1a, align2a, scorea = run_aleigen(contacts1,
# contacts2, num_v)
align1, align2, score = optimal_cmo(tad1, tad2, num_v)
align1b = []
align2b = []
for c in range(len(align1)):
if align1[c] != '-' and align2[c] != '-':
align1b.append(align1[c])
align2b.append(align2[c])
print('=' * 80)
print(''.join(['{:>5}'.format(i) for i in range(len(tad1))]))
print('\n'.join(
[''.join(['{:>5}'.format(round(j, 2)) for j in i]) for i in tad1]))
print('-' * 80)
print(''.join(['{:>5}'.format(i) for i in range(len(tad2))]))
print('\n'.join(
[''.join(['{:>5}'.format(round(j, 2)) for j in i]) for i in tad2]))
print('=' * 80)
#print ''.join(['{:>4}'.format(a) for a in align1a])
#print ''.join(['{:>4}'.format(a) for a in align2a])
print('-' * 80)
print(''.join(['{:>4}'.format(a) for a in align1b]))
print(''.join(['{:>4}'.format(a) for a in align2b]))
print('=' * 80)
def test_06_tad_clustering(self):
if ONLY and ONLY != "06":
return
if CHKTIME:
t0 = time()
test_chr = Chromosome(
name="Test Chromosome",
experiment_tads=[exp4],
experiment_names=["exp1"],
experiment_hic_data=[PATH + "/20Kb/chrT/chrT_D.tsv"],
experiment_resolutions=[20000, 20000],
silent=True,
)
all_tads = []
for _, tad in test_chr.iter_tads("exp1", normed=False):
all_tads.append(tad)
# align1, align2, _ = optimal_cmo(all_tads[7], all_tads[10], 7,
# method='score')
align1, align2, _ = optimal_cmo(all_tads[1], all_tads[3], 7, method="score")
# Values with square root normalization.
# self.assertEqual(align1, [0, 1, '-', 2, 3, '-', 4, 5, 6, 7, 8, 9, 10])
# self.assertEqual(align2,[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12])
self.assertEqual(align1, [0, 1, 2, "-", "-", 3, 4, 5, 6, 7, 8, "-", 9])
self.assertEqual(align2, [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12])
if CHKTIME:
print "6", time() - t0
def test_06_tad_clustering(self):
if CHKTIME:
t0 = time()
test_chr = Chromosome(name='Test Chromosome',
experiment_tads=[exp4],
experiment_names=['exp1'],
experiment_hic_data=[
PATH + '/20Kb/chrT/chrT_D.tsv'],
experiment_resolutions=[20000,20000],
silent=True)
all_tads = []
for _, tad in test_chr.iter_tads('exp1'):
all_tads.append(tad)
#align1, align2, _ = optimal_cmo(all_tads[7], all_tads[10], 7,
# method='score')
align1, align2, _ = optimal_cmo(all_tads[1], all_tads[3], 7,
method='score')
# Values with square root normalization.
#self.assertEqual(align1, [0, 1, '-', 2, 3, '-', 4, 5, 6, 7, 8, 9, 10])
#self.assertEqual(align2,[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12])
self.assertEqual(align1, [0, 1, 2, '-', '-', 3, 4, 5, 6, 7, 8, '-', 9])
self.assertEqual(align2, [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12])
if CHKTIME:
print '6', time() - t0
def main():
"""
main function
"""
tad1, tad2, contacts1, contacts2 = generate_random_contacts(size=12,
prob_mut=0.5,
num_changes=2)
size1 = len(tad1)
size2 = len(tad2)#max([max(c) for c in contacts2])
num_v = min(size1, size2)
#align1a, align2a, scorea = run_aleigen(contacts1,
# contacts2, num_v)
align1, align2, score = optimal_cmo(tad1, tad2, num_v)
align1b = []
align2b = []
for c in xrange(len(align1)):
if align1[c] != '-' and align2[c] != '-':
align1b.append(align1[c])
align2b.append(align2[c])
print '='*80
print ''.join(['{:>5}'.format(i) for i in range(len(tad1))])
print '\n'.join([''.join(['{:>5}'.format(round(j, 2)) for j in i]) for i in tad1])
print '-'*80
print ''.join(['{:>5}'.format(i) for i in range(len(tad2))])
print '\n'.join([''.join(['{:>5}'.format(round(j, 2)) for j in i]) for i in tad2])
print '='*80
#print ''.join(['{:>4}'.format(a) for a in align1a])
#print ''.join(['{:>4}'.format(a) for a in align2a])
print '-'*80
print ''.join(['{:>4}'.format(a) for a in align1b])
print ''.join(['{:>4}'.format(a) for a in align2b])
print '='*80
def tad_clustering(self):
test_chr = Chromosome(name="Test Chromosome", resolution=20000)
test_chr.add_experiment("chrT/chrT_A.tsv", name="exp1")
test_chr.find_TAD(["exp1"])
all_tads = list(test_chr.iter_tads("exp1"))
align1, align2 = optimal_cmo(all_tads[4], all_tads[8], 9)
self.assertEqual(align1, [1, 2, "-", "-", "-", "-", 3, "-", 4, 5, 6, "-", 7, 8])
self.assertEqual(align2, [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15])
def compareTwoTADs():
from pytadbit.tad_clustering.tad_cmo import optimal_cmo
tad1 = list(my_chrom.iter_tads('Control'))[31]
tad2 = list(my_chrom.iter_tads('Control'))[35]
align1, align2, score = optimal_cmo(tad1[1],
tad2[1],
max_num_v=8,
long_nw=True,
long_dist=True,
method='frobenius')
def test_06_tad_clustering(self):
test_chr = Chromosome(name='Test Chromosome',
experiment_tads=[exp4],
experiment_names=['exp1'],
experiment_hic_data=['20Kb/chrT/chrT_D.tsv'],
experiment_resolutions=[20000,20000])
all_tads = []
for _, tad in test_chr.iter_tads('exp1'):
all_tads.append(tad)
align1, align2, _ = optimal_cmo(all_tads[7], all_tads[10], 7,
method='score')
self.assertEqual(align1, [0, 1, '-', 2, 3, '-', 4, 5, 6, 7, 8, 9, 10])
self.assertEqual(align2,[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12])
cond2 = lambda x: x['pos'] > 50
print ali.get_column(cond1=cond1, cond2=cond2)
print ali.get_column(cond1=cond1, cond2=cond2, min_num=1)
exp = my_chrom.experiments[0]
tad1 = list(my_chrom.iter_tads('First Hi-C experiment'))[41]
tad2 = list(my_chrom.iter_tads('First Hi-C experiment'))[39]
from pytadbit.tad_clustering.tad_cmo import optimal_cmo
align1, align2, score = optimal_cmo(tad1[1], tad2[1], max_num_v=8, long_nw=True, long_dist=True, method='frobenius')
from pytadbit.tad_clustering.tad_cmo import merge_tads
matrix1, matrix2, matrix_merged = merge_tads(tad1[1], tad2[1], align1, align2)
from matplotlib import pyplot as plt
from numpy import log2
cmap = plt.get_cmap()
cmap.set_bad(color = 'k', alpha = .7)
plt.subplot(2, 2, 2)
plt.imshow(log2(matrix1), origin='lower', interpolation="nearest")
