def test_write_2(self):
msa = [
">d1a1x__ b.63.1.1 (-) p13-MTCP1 {Human (H**o sapiens)}",
"PPDHLWVHQEGIYRDEYQRTWVAVVEEETSFLRARVQQIQVPLGDAARPSHLLTSQL",
">gi|6678257|ref|NP_033363.1|:(7-103) T-cell lymphoma breakpoint 1 [Mus musculus]",
"HPNRLWIWEKHVYLDEFRRSWLPVVIKSNEKFQVILRQEDVTLGEAMSPSQLVPYEL",
">gi|7305557|ref|NP_038800.1|:(8-103) T-cell leukemia/lymphoma 1B, 3 [Mus musculus]",
"PPRFLVCTRDDIYEDENGRQWVVAKVETSRSpygsrietcITVHLQHMTTIPQEPTPQQPINNNSL",
">gi|11415028|ref|NP_068801.1|:(2-106) T-cell lymphoma-1; T-cell lymphoma-1A [H**o sapiens]",
"HPDRLWAWEKFVYLDEKQHAWLPLTIEikDRLQLRVLLRREDVVLGRPMTPTQIGPSLL",
">gi|7305561|ref|NP_038804.1|:(7-103) T-cell leukemia/lymphoma 1B, 5 [Mus musculus]",
"----------GIYEDEHHRVWIAVNVETSHSSHgnrietcvtVHLQHMTTLPQEPTPQQPINNNSL",
">gi|7305553|ref|NP_038801.1|:(5-103) T-cell leukemia/lymphoma 1B, 1 [Mus musculus]",
"LPVYLVSVRLGIYEDEHHRVWIVANVETshSSHGNRRRTHVTVHLWKLIPQQVIPFNplnydFL",
">gi|27668591|ref|XP_234504.1|:(7-103) similar to Chain A, Crystal Structure Of Murine Tcl1",
"-PDRLWLWEKHVYLDEFRRSWLPIVIKSNGKFQVIMRQKDVILGDSMTPSQLVPYEL",
">gi|27668589|ref|XP_234503.1|:(9-91) similar to T-cell leukemia/lymphoma 1B, 5;",
"-PHILTLRTHGIYEDEHHRLWVVLDLQAShlSFSNRLLIYLTVYLQqgvafplESTPPSPMNLNGL",
">gi|7305559|ref|NP_038802.1|:(8-102) T-cell leukemia/lymphoma 1B, 4 [Mus musculus]",
"PPCFLVCTRDDIYEDEHGRQWVAAKVETSSHSPycskietcvtVHLWQMTTLFQEPSPDSLKTFNFL",
">gi|7305555|ref|NP_038803.1|:(9-102) T-cell leukemia/lymphoma 1B, 2 [Mus musculus]",
"---------PGFYEDEHHRLWMVAKLETCSHSPycnkietcvtVHLWQMTRYPQEPAPYNPMNYNFL",
]
f_name_in = create_tmp_f(content=os.linesep.join(msa))
f_name_out = create_tmp_f()
parser = A3mParser()
with open(f_name_in, 'r') as f_in, open(f_name_out, 'w') as f_out:
sequence_file = parser.read(f_in, remove_insert=False)
parser.write(f_out, sequence_file)
ref = [
">d1a1x__ b.63.1.1 (-) p13-MTCP1 {Human (H**o sapiens)}",
"PPDHLWVHQEGIYRDEYQRTWVAVVEE--E--T--SF---------LR----------ARVQQIQVPLG-------DAARPSHLLTS-----QL",
">gi|6678257|ref|NP_033363.1|:(7-103) T-cell lymphoma breakpoint 1 [Mus musculus]",
"HPNRLWIWEKHVYLDEFRRSWLPVVIK--S--N--EK---------FQ----------VILRQEDVTLG-------EAMSPSQLVPY-----EL",
">gi|7305557|ref|NP_038800.1|:(8-103) T-cell leukemia/lymphoma 1B, 3 [Mus musculus]",
"PPRFLVCTRDDIYEDENGRQWVVAKVE--T--S--RSpygsrietcIT----------VHLQHMTTIPQ-------EPTPQQPINNN-----SL",
">gi|11415028|ref|NP_068801.1|:(2-106) T-cell lymphoma-1; T-cell lymphoma-1A [H**o sapiens]",
"HPDRLWAWEKFVYLDEKQHAWLPLTIEikD--R--LQ---------LR----------VLLRREDVVLG-------RPMTPTQIGPS-----LL",
">gi|7305561|ref|NP_038804.1|:(7-103) T-cell leukemia/lymphoma 1B, 5 [Mus musculus]",
"----------GIYEDEHHRVWIAVNVE--T--S--HS---------SHgnrietcvt-VHLQHMTTLPQ-------EPTPQQPINNN-----SL",
">gi|7305553|ref|NP_038801.1|:(5-103) T-cell leukemia/lymphoma 1B, 1 [Mus musculus]",
"LPVYLVSVRLGIYEDEHHRVWIVANVE--TshS--SH---------GN----------RRRTHVTVHLW-------KLIPQQVIPFNplnydFL",
">gi|27668591|ref|XP_234504.1|:(7-103) similar to Chain A, Crystal Structure Of Murine Tcl1",
"-PDRLWLWEKHVYLDEFRRSWLPIVIK--S--N--GK---------FQ----------VIMRQKDVILG-------DSMTPSQLVPY-----EL",
">gi|27668589|ref|XP_234503.1|:(9-91) similar to T-cell leukemia/lymphoma 1B, 5;",
"-PHILTLRTHGIYEDEHHRLWVVLDLQ--A--ShlSF---------SN----------RLLIYLTVYLQqgvafplESTPPSPMNLN-----GL",
">gi|7305559|ref|NP_038802.1|:(8-102) T-cell leukemia/lymphoma 1B, 4 [Mus musculus]",
"PPCFLVCTRDDIYEDEHGRQWVAAKVE--T--S--SH---------SPycskietcvtVHLWQMTTLFQ-------EPSPDSLKTFN-----FL",
">gi|7305555|ref|NP_038803.1|:(9-102) T-cell leukemia/lymphoma 1B, 2 [Mus musculus]",
"---------PGFYEDEHHRLWMVAKLE--T--C--SH---------SPycnkietcvtVHLWQMTRYPQ-------EPAPYNPMNYN-----FL",
"",
]
ref = os.linesep.join(ref)
with open(f_name_out, 'r') as f_in:
output = "".join(f_in.readlines())
self.assertEqual(ref, output)
os.unlink(f_name_in)
os.unlink(f_name_out)
def test_read_3(self):
msa = """CLUSTAL FORMAT for
seq_0 AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
seq_1 BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB
seq_2 CCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC
seq_0 AAAAAAAAA
seq_1 BBBBBBBBB
seq_2 CCCCCCCCC
"""
f_name = create_tmp_f(content=msa)
parser = ClustalParser()
with open(f_name, 'r') as f_in:
sequence_file = parser.read(f_in)
for i, sequence_entry in enumerate(sequence_file):
if i == 0:
self.assertEqual('seq_0', sequence_entry.id)
self.assertEqual(
'AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA',
sequence_entry.seq)
elif i == 1:
self.assertEqual('seq_1', sequence_entry.id)
self.assertEqual(
'BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB',
sequence_entry.seq)
elif i == 2:
self.assertEqual('seq_2', sequence_entry.id)
self.assertEqual(
'CCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC',
sequence_entry.seq)
os.unlink(f_name)
def test_read_1(self):
content = """1,2,0.12212
1,3,0.14004
1,4,0.12926
1,5,0.089211
1,6,0.079976
1,7,0.078954
1,8,0.052275
1,9,0.026012
1,10,0.049844
1,11,0.045109
"""
f_name = create_tmp_f(content=content)
with open(f_name, 'r') as f_in:
contact_file = PlmDCAParser().read(f_in)
contact_map1 = contact_file.top_map
self.assertEqual(1, len(contact_file))
self.assertEqual(10, len(contact_map1))
self.assertEqual([1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
[c.res1_seq for c in contact_map1])
self.assertEqual([2, 3, 4, 5, 6, 7, 8, 9, 10, 11],
[c.res2_seq for c in contact_map1])
self.assertEqual([
0.12212, 0.14004, 0.12926, 0.089211, 0.079976, 0.078954, 0.052275,
0.026012, 0.049844, 0.045109
], [c.raw_score for c in contact_map1])
os.unlink(f_name)
def test_read_2(self):
content = """# Check one two
Hello WOrld
1 2 0.93514
1 3 0.67324
1 4 0.23692
1 5 0.13166
1 6 0.09188
1 7 0.07957
1 8 0.06556
1 9 0.05188
1 10 0.04146
1 11 0.03264
1 12 0.02515
1 13 0.02137
1 14 0.01961
1 15 0.01710
1 16 0.01397
1 17 0.01192
"""
f_name = create_tmp_f(content=content)
with open(f_name, 'r') as f_in:
contact_file = PconsParser().read(f_in)
contact_map1 = contact_file.top_map
self.assertEqual(1, len(contact_file))
self.assertEqual(16, len(contact_map1))
self.assertEqual([1] * 16, [c.res1_seq for c in contact_map1])
self.assertEqual(list(range(2, 18)),
[c.res2_seq for c in contact_map1])
self.assertEqual([0.93514, 0.67324, 0.23692, 0.13166, 0.09188],
[c.raw_score for c in contact_map1][:5])
os.unlink(f_name)
def test_write_1(self):
contact_file = ContactFile('RR')
contact_file.target = 'R9999'
contact_file.author = '1234-5678-9000'
contact_file.remark = ['Predictor remarks']
contact_file.method = [
'Description of methods used', 'Description of methods used'
]
contact_map = ContactMap('1')
contact_file.add(contact_map)
for c in [(1, 9, 0, 8, 0.7), (1, 10, 0, 8, 0.7), (2, 8, 0, 8, 0.9),
(3, 12, 0, 8, 0.4)]:
contact = Contact(c[0], c[1], c[4], distance_bound=(c[2], c[3]))
contact_map.add(contact)
contact_map.sequence = Sequence('1',
'HLEGSIGILLKKHEIVFDGCHDFGRTYIWQMSD')
contact_map.set_sequence_register()
f_name = create_tmp_f()
with open(f_name, 'w') as f_out:
ComsatParser().write(f_out, contact_file)
content = [
"1 H 9 L Hx-Hx",
"1 H 10 L Hx-Hx",
"2 L 8 I Hx-Hx",
"3 E 12 K Hx-Hx",
]
with open(f_name, 'r') as f_in:
output = f_in.read().splitlines()
self.assertEqual(content, output)
os.unlink(f_name)
def test_read_1(self):
content = """5 I 9 Q 0.000 0.286 0.185 0.836 0.875 0.749
5 I 10 R 0.000 0.000 0.105 0.875 0.482 0.634
5 I 11 I 0.000 0.178 0.066 0.730 0.876 0.727
5 I 21 I 0.030 0.021 0.233 0.645 0.733 0.557
5 I 58 G 0.000 0.054 0.010 0.642 0.799 0.535
6 T 62 V 0.000 0.000 0.027 0.485 0.428 0.585
6 T 63 S 0.000 0.004 0.051 0.547 0.387 0.529
6 T 78 L 0.000 0.000 0.039 0.624 0.384 0.581
6 T 79 T 0.000 0.000 0.036 0.657 0.415 0.679
6 T 80 I 0.000 0.076 0.003 0.513 0.386 0.578
6 T 94 Q 0.000 0.068 0.041 0.534 0.489 0.679
"""
f_name = create_tmp_f(content=content)
with open(f_name, 'r') as f_in:
contact_file = BCLContactParser().read(f_in)
contact_map1 = contact_file.top_map
self.assertEqual(1, len(contact_file))
self.assertEqual(11, len(contact_map1))
self.assertEqual([5, 5, 5, 5, 5, 6, 6, 6, 6, 6, 6],
[c.res1_seq for c in contact_map1])
self.assertEqual([9, 10, 11, 21, 58, 62, 63, 78, 79, 80, 94],
[c.res2_seq for c in contact_map1])
self.assertEqual([
0.749, 0.634, 0.727, 0.557, 0.535, 0.585, 0.529, 0.581, 0.679,
0.578, 0.679
], [c.raw_score for c in contact_map1])
os.unlink(f_name)
def test_write_1(self):
contact_file = ContactFile('RR')
contact_file.target = 'R9999'
contact_file.author = '1234-5678-9000'
contact_file.remark = ['Predictor remarks']
contact_file.method = ['Description of methods used', 'Description of methods used']
contact_map = ContactMap('1')
contact_file.add(contact_map)
for c in [(1, 9, 0, 8, 0.7), (1, 10, 0, 8, 0.7), (2, 8, 0, 8, 0.9), (3, 12, 0, 8, 0.4)]:
contact = Contact(c[0], c[1], c[4], distance_bound=(c[2], c[3]))
contact_map.add(contact)
contact_map.sequence = Sequence('1', 'HLEGSIGILLKKHEIVFDGCHDFGRTYIWQMSD')
contact_map.assign_sequence_register()
f_name = create_tmp_f()
with open(f_name, 'w') as f_out:
PsicovParser().write(f_out, contact_file)
content = [
"1 9 0 8 0.700000",
"1 10 0 8 0.700000",
"2 8 0 8 0.900000",
"3 12 0 8 0.400000",
"",
]
content = os.linesep.join(content)
with open(f_name, 'r') as f_in:
data = "".join(f_in.readlines())
self.assertEqual(content, data)
os.unlink(f_name)
def test_read_1(self):
content = """PFRMAT RR
TARGET R9999
AUTHOR 1234-5678-9000
REMARK Predictor remarks
METHOD Description of methods used
METHOD Description of methods used
MODEL 1
HLEGSIGILLKKHEIVFDGC
HDFGRTYIWQMSD
1 9 0 8 0.70
1 10 0 8 0.70
1 12 0 8 0.60
2 8 0 8 0.90
3 7 0 8 0.70
3 12 0 8 0.40
4 6 0 8 0.90
7 14 0 8 0.30
9 14 0 8 0.50
END
"""
f_name = create_tmp_f(content=content)
with open(f_name, 'r') as f_in:
contact_file = CaspParser().read(f_in)
contact_map1 = contact_file.top_map
self.assertEqual(1, len(contact_file))
self.assertEqual(9, len(contact_map1))
self.assertEqual("HLEGSIGILLKKHEIVFDGCHDFGRTYIWQMSD",
contact_map1.sequence.seq)
self.assertEqual("HLEG-IGILL-K-E-------------------",
contact_map1.repr_sequence.seq)
os.unlink(f_name)
def test_read_3(self):
content = """ATOM 1 N TYR A 36 39.107 51.628 3.103 0.50 43.13 N
ATOM 2 CA TYR A 36 38.300 50.814 2.204 0.50 41.80 C
ATOM 3 O TYR A 36 38.712 48.587 1.405 0.50 41.03 O
ATOM 4 CB TYR A 36 37.586 51.694 1.175 0.50 41.61 C
ATOM 5 N PHE A 86 32.465 47.498 5.487 0.50 25.81 N
ATOM 6 CA PHE A 86 32.670 48.303 4.288 0.50 26.45 C
ATOM 7 O PHE A 86 31.469 50.326 3.758 0.50 28.47 O
ATOM 8 CB PHE A 86 32.977 47.392 3.090 0.50 25.35 C
ATOM 9 N TRP A 171 23.397 37.507 -1.161 0.50 18.04 N
ATOM 10 CA TRP A 171 23.458 36.846 0.143 0.50 20.46 C
ATOM 11 O TRP A 171 22.235 34.954 0.951 0.50 22.45 O
ATOM 12 CB TRP A 171 23.647 37.866 1.275 0.50 18.83 C
ATOM 13 N PHE A 208 32.221 42.624 -5.829 0.50 19.96 N
ATOM 14 CA PHE A 208 31.905 43.710 -4.909 0.50 20.31 C
ATOM 15 O PHE A 208 32.852 45.936 -5.051 0.50 17.69 O
ATOM 16 CB PHE A 208 31.726 43.102 -3.518 0.50 19.90 C
END
"""
f_name = create_tmp_f(content=content)
with open(f_name, 'r') as f_in:
contact_file = PdbParser().read(f_in,
distance_cutoff=7,
atom_type='CB')
contact_map1 = contact_file.top_map
self.assertEqual(1, len(contact_file))
self.assertEqual(1, len(contact_map1))
self.assertEqual([36],
[c.res1_seq for c in contact_map1 if c.true_positive])
self.assertEqual([86],
[c.res2_seq for c in contact_map1 if c.true_positive])
self.assertEqual(
[0.934108], [c.raw_score for c in contact_map1 if c.true_positive])
os.unlink(f_name)
def test_write_2(self):
seq = [
"# Hello World",
">00FAF_A|<unknown description>",
"GSMFTPKPPQDSAVIKAGYCVKQGAVMKNWKRRYFQLDENTIGYFKSELEKEPLRVIPLK",
]
f_name_in = create_tmp_f(content='\n'.join(seq))
f_name_out = create_tmp_f()
parser = FastaParser()
with open(f_name_in, 'r') as f_in, open(f_name_out, 'w') as f_out:
sequence_file = parser.read(f_in)
parser.write(f_out, sequence_file)
with open(f_name_out, 'r') as f_in:
output = f_in.read().splitlines()
self.assertEqual(seq, output)
map(os.unlink, [f_name_in, f_name_out])
def test_read_1(self):
msa = """GSMFTPKPPQDSAVI--GYCVKQGAVMKNWKRRY--LDENTIGYF
EVHK--ECKQSDIMMRD--FEIVTTSRTFYVQADSPEEMHSWIKA
EVHKVQECK--DIMMRDNLFEI--TSRTFWKRRY--LDENTIGYF
EVHKVQECK--DIMMRDNLFEI--TSRTF--RRY--LDENTIGYF
"""
f_name = create_tmp_f(content=msa)
parser = A2mParser()
with open(f_name, 'r') as f_in:
sequence_file = parser.read(f_in)
for i, sequence_entry in enumerate(sequence_file):
if i == 0:
self.assertEqual('seq_0', sequence_entry.id)
self.assertEqual(
'GSMFTPKPPQDSAVI--GYCVKQGAVMKNWKRRY--LDENTIGYF',
sequence_entry.seq)
elif i == 1:
self.assertEqual('seq_1', sequence_entry.id)
self.assertEqual(
'EVHK--ECKQSDIMMRD--FEIVTTSRTFYVQADSPEEMHSWIKA',
sequence_entry.seq)
elif i == 2:
self.assertEqual('seq_2', sequence_entry.id)
self.assertEqual(
'EVHKVQECK--DIMMRDNLFEI--TSRTFWKRRY--LDENTIGYF',
sequence_entry.seq)
elif i == 3:
self.assertEqual('seq_3', sequence_entry.id)
self.assertEqual(
'EVHKVQECK--DIMMRDNLFEI--TSRTF--RRY--LDENTIGYF',
sequence_entry.seq)
os.unlink(f_name)
def test_read_1(self):
content = """46 78 0 8 9.301869
80 105 0 8 8.856009
111 129 0 8 7.252451
75 205 0 8 6.800462
19 44 0 8 6.588349
111 130 0 8 6.184269
23 41 0 8 6.163786
171 205 0 8 5.519271
53 126 0 8 5.440612
100 140 0 8 5.382865
"""
f_name = create_tmp_f(content=content)
with open(f_name, 'r') as f_in:
contact_file = PsicovParser().read(f_in)
contact_map1 = contact_file.top_map
self.assertEqual(1, len(contact_file))
self.assertEqual(10, len(contact_map1))
self.assertEqual([46, 80, 111, 75, 19, 111, 23, 171, 53, 100], [c.res1_seq for c in contact_map1])
self.assertEqual([78, 105, 129, 205, 44, 130, 41, 205, 126, 140], [c.res2_seq for c in contact_map1])
self.assertEqual(
[9.301869, 8.856009, 7.252451, 6.800462, 6.588349, 6.184269, 6.163786,
5.519271, 5.440612, 5.382865],
[c.raw_score for c in contact_map1]
)
os.unlink(f_name)
def test_read_3(self):
content = """i j gene i_id j_id r_sco s_sco prob I_prob
127 187 A 127_V 187_I 0.183 3.635 1.000 N/A
83 87 A 83_E 87_Q 0.183 3.633 1.000 N/A
108 111 A 108_P 111_P 0.105 2.095 0.989 N/A
431 435 B 241_L 245_L 0.104 2.076 0.988 N/A
63 83 A 63_T 83_E 0.098 1.952 0.980 N/A
23 434 AB 23_T 244_L 0.082 1.624 0.924 0.519
20 438 AB 20_Y 248_T 0.059 1.178 0.647 0.181
265 275 B 75_E 85_V 0.059 1.175 0.644 N/A
263 267 B 73_A 77_G 0.059 1.172 0.641 N/A
19 438 AB 19_L 248_T 0.059 1.17 0.640 0.176
211 215 B 21_D 25_A 0.054 1.069 0.536 N/A
30 65 A 30_A 65_T 0.054 1.065 0.532 N/A
24 434 AB 24_A 244_L 0.054 1.064 0.531 0.123
"""
f_name = create_tmp_f(content=content)
with open(f_name, 'r') as f_in:
contact_file = GremlinParser().read(f_in)
self.assertEqual(3, len(contact_file))
chain_a_res1seq = [127, 83, 108, 63, 30]
chain_a_rawscore = [0.183, 0.183, 0.105, 0.098, 0.054]
chain_b_res1seq = [431, 265, 263, 211]
chain_b_rawscore = [0.104, 0.059, 0.059, 0.054]
chain_ab_res1seq = [23, 20, 19, 24]
chain_ab_rawscore = [0.082, 0.059, 0.059, 0.054]
for count, res1_seqs, raw_scores, cmap in zip([5, 4, 4],
[chain_a_res1seq, chain_ab_res1seq, chain_b_res1seq],
[chain_a_rawscore, chain_ab_rawscore, chain_b_rawscore],
contact_file):
self.assertEqual(count, len(cmap))
self.assertEqual(res1_seqs, [c.res1_seq for c in cmap])
self.assertEqual(raw_scores, [c.raw_score for c in cmap])
os.unlink(f_name)
def test_write_6(self):
contact_file = ContactFile('RR')
contact_map = ContactMap('1')
contact_file.add(contact_map)
for c in [('A', 1, 'B', 9, 0, 8, 0.7), ('A', 1, 'B', 10, 0, 8, 0.7),
('A', 2, 'B', 8, 0, 8, 0.9), ('A', 3, 'B', 12, 0, 8, 0.4)]:
contact = Contact(c[1], c[3], c[6], distance_bound=(c[4], c[5]))
contact.res1_chain = c[0]
contact.res2_chain = c[2]
contact_map.add(contact)
contact_map.sequence = Sequence(
'1',
'HLEGSIGILLKKHEIVFDGCHDFGRTYIWQMSDHLEGSIGILLKKHEIVFDGCHDFGRTYIWQMSD'
)
f_name = create_tmp_f()
with open(f_name, 'w') as f_out:
CaspParser().write(f_out, contact_file)
content = [
"PFRMAT RR",
"MODEL 1",
"HLEGSIGILLKKHEIVFDGCHDFGRTYIWQMSDHLEGSIGILLKKHEIVF",
"DGCHDFGRTYIWQMSD",
"A1 B9 0 8 0.700000",
"A1 B10 0 8 0.700000",
"A2 B8 0 8 0.900000",
"A3 B12 0 8 0.400000",
"ENDMDL",
"END",
]
with open(f_name, 'r') as f_in:
output = f_in.read().splitlines()
self.assertEqual(content, output)
os.unlink(f_name)
def test_write_1(self):
contact_file = ContactFile('test')
contact_map = ContactMap('A')
contact_file.add(contact_map)
for c in [(1, 9, 0, 8, 0.7), (1, 10, 0, 8, 0.7), (2, 8, 0, 8, 0.9), (3, 12, 0, 8, 0.4)]:
contact = Contact(c[0], c[1], c[4], distance_bound=(c[2], c[3]))
contact_map.add(contact)
contact_map.sequence = Sequence('1', 'HLEGSIGILLKKHEIVFDGCHDFGRTYIWQMSDHLEGSIGILLKKHEIVFDGCHDFGRTYIWQMSD')
contact_map.assign_sequence_register()
f_name = create_tmp_f()
with open(f_name, 'w') as f_out:
GremlinParser().write(f_out, contact_file)
content = [
"i j i_id j_id r_sco s_sco prob",
"1 9 1_H 9_L 0.7 1.0 1.0",
"1 10 1_H 10_L 0.7 1.0 1.0",
"2 8 2_L 8_I 0.9 1.3 1.0",
"3 12 3_E 12_K 0.4 0.6 1.0",
"",
]
content = os.linesep.join(content)
with open(f_name, 'r') as f_in:
data = "".join(f_in.readlines())
self.assertEqual(content, data)
os.unlink(f_name)
def test_read_2(self):
content = """# Some comments
# That are here for whatever reason
i j i_id j_id r_sco s_sco prob
179 246 179_C 246_L 0.2019 4.740 1.000
262 305 262_G 305_Y 0.1742 4.090 1.000
428 448 428_A 448_N 0.1638 3.846 1.000
214 231 214_F 231_V 0.1342 3.150 1.000
457 488 457_L 488_Y 0.1254 2.945 1.000
220 223 220_A 223_A 0.1187 2.786 0.999
143 209 143_I 209_D 0.1139 2.674 0.999
79 365 79_M 365_I 0.1114 2.615 0.998
215 268 215_V 268_A 0.1109 2.604 0.998
262 266 262_G 266_K 0.1040 2.442 0.997
"""
f_name = create_tmp_f(content=content)
with open(f_name, 'r') as f_in:
contact_file = GremlinParser().read(f_in)
contact_map1 = contact_file.top_map
self.assertEqual(1, len(contact_file))
self.assertEqual(10, len(contact_map1))
self.assertEqual(
[179, 262, 428, 214, 457, 220, 143, 79, 215, 262],
[c.res1_seq for c in contact_map1]
)
self.assertEqual(
[0.2019, 0.1742, 0.1638, 0.1342, 0.1254, 0.1187, 0.1139, 0.1114, 0.1109, 0.1040],
[c.raw_score for c in contact_map1]
)
os.unlink(f_name)
def test_write_1(self):
contact_file = ContactFile('test')
contact_map = ContactMap('1')
contact_file.add(contact_map)
for c in [(1, 9, 0, 8, 0.7), (1, 10, 0, 8, 0.7), (2, 8, 0, 8, 0.9),
(3, 12, 0, 8, 0.4)]:
contact = Contact(c[0], c[1], c[4], distance_bound=(c[2], c[3]))
contact_map.add(contact)
contact_map.sequence = Sequence(
'1',
'HLEGSIGILLKKHEIVFDGCHDFGRTYIWQMSDHLEGSIGILLKKHEIVFDGCHDFGRTYIWQMSD'
)
f_name = create_tmp_f()
# Not sure if bug in Python3 numpy or intended purpose [Implemented: 21.11.2016]
mode = 'wb' if sys.version_info.major == 3 else 'w'
with open(f_name, mode) as f_out:
CCMpredParser().write(f_out, contact_file)
content = [
'0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t6.999999999999999556e-01\t6.999999999999999556e-01\t0.000000000000000000e+00\t0.000000000000000000e+00',
'0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t9.000000000000000222e-01\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00',
'0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t4.000000000000000222e-01',
'0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00',
'0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00',
'0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00',
'0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00',
'0.000000000000000000e+00\t9.000000000000000222e-01\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00',
'6.999999999999999556e-01\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00',
'6.999999999999999556e-01\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00',
'0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00',
'0.000000000000000000e+00\t0.000000000000000000e+00\t4.000000000000000222e-01\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00\t0.000000000000000000e+00'
]
with open(f_name, 'r') as f_in:
output = f_in.read().splitlines()
self.assertEqual(content, output)
os.unlink(f_name)
def test_read_3(self):
msa = """#foo
#bar
>seq1
GSMFTPKPPQDSAVIKAGYCVKQGAVMKNWKRRYFQLDENTIGYF
>seq2
EVHKVQECKQSDIMMRDNLFEIVTTSRTFYVQADSPEEMHSWIKA
>seq3
EVHKVQECKQSDIMMRDNLFEIVTTSRTFWKRRYFQLDENTIGYF
"""
f_name = create_tmp_f(content=msa)
parser = FastaParser()
with open(f_name, 'r') as f_in:
sequence_file = parser.read(f_in)
self.assertEqual(['foo', 'bar'], sequence_file.remark)
for i, sequence_entry in enumerate(sequence_file):
if i == 0:
self.assertEqual('seq1', sequence_entry.id)
self.assertEqual(
'GSMFTPKPPQDSAVIKAGYCVKQGAVMKNWKRRYFQLDENTIGYF',
sequence_entry.seq)
elif i == 1:
self.assertEqual('seq2', sequence_entry.id)
self.assertEqual(
'EVHKVQECKQSDIMMRDNLFEIVTTSRTFYVQADSPEEMHSWIKA',
sequence_entry.seq)
elif i == 2:
self.assertEqual('seq3', sequence_entry.id)
self.assertEqual(
'EVHKVQECKQSDIMMRDNLFEIVTTSRTFWKRRYFQLDENTIGYF',
sequence_entry.seq)
os.unlink(f_name)
def test_read_1(self):
content = """Helix Position Residue Helix Position Residue Probability
H1 30 F H2 55 F 1.000000
H1 33 L H2 51 A 0.944091
H1 18 G H2 65 C 0.942259
H1 30 F H2 54 G 0.919241
H1 26 I H2 57 L 0.817638
H1 18 G H2 58 S 0.797449
H1 33 L H2 63 L 0.795520
H1 12 A H2 68 V 0.795462
H1 29 V H2 55 F 0.791829
H1 24 I H2 51 A 0.790044
H1 19 L H2 62 G 0.784613
H1 19 L H2 55 F 0.782741
"""
f_name = create_tmp_f(content=content)
with open(f_name, 'r') as f_in:
contact_file = MemBrainParser().read(f_in)
contact_map1 = contact_file.top_map
self.assertEqual(1, len(contact_file))
self.assertEqual(12, len(contact_map1))
self.assertEqual([30, 33, 18, 30, 26, 18, 33, 12, 29, 24, 19, 19],
[c.res1_seq for c in contact_map1])
self.assertEqual([55, 51, 65, 54, 57, 58, 63, 68, 55, 51, 62, 55],
[c.res2_seq for c in contact_map1])
self.assertEqual([
1.000000, 0.944091, 0.942259, 0.919241, 0.817638, 0.797449,
0.795520, 0.795462, 0.791829, 0.790044, 0.784613, 0.782741
], [c.raw_score for c in contact_map1])
os.unlink(f_name)
def test_write_3(self):
contact_file = ContactFile('RR')
contact_map = ContactMap('1')
contact_file.add(contact_map)
for c in [(1, 9, 0, 8, 0.7), (1, 10, 0, 8, 0.7), (2, 8, 0, 8, 0.9),
(3, 12, 0, 8, 0.4)]:
contact = Contact(c[0], c[1], c[4], distance_bound=(c[2], c[3]))
contact_map.add(contact)
f_name = create_tmp_f()
with open(f_name, 'w') as f_out:
CaspParser().write(f_out, contact_file)
content = [
"PFRMAT RR",
"MODEL 1",
"1 9 0 8 0.700000",
"1 10 0 8 0.700000",
"2 8 0 8 0.900000",
"3 12 0 8 0.400000",
"ENDMDL",
"END",
]
with open(f_name, 'r') as f_in:
output = f_in.read().splitlines()
self.assertEqual(content, output)
os.unlink(f_name)
def test_read_1(self):
content = """1 M 2 V 0.0338619 0
1 M 3 G 0.0307956 0
1 M 4 L 0.0268079 0
1 M 5 T 0.0219783 0
1 M 6 T 0.0222061 0
1 M 7 L 0.0213079 0
1 M 8 F 0.0119054 0
1 M 9 W 0.0275182 0
1 M 10 L 0.0134577 0
1 M 11 G 0.0234555 0
"""
f_name = create_tmp_f(content=content)
with open(f_name, 'r') as f_in:
contact_file = FreeContactParser().read(f_in)
contact_map1 = contact_file.top_map
self.assertEqual(1, len(contact_file))
self.assertEqual(10, len(contact_map1))
self.assertEqual([1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
[c.res1_seq for c in contact_map1])
self.assertEqual([2, 3, 4, 5, 6, 7, 8, 9, 10, 11],
[c.res2_seq for c in contact_map1])
self.assertEqual([
0.0338619, 0.0307956, 0.0268079, 0.0219783, 0.0222061, 0.0213079,
0.0119054, 0.0275182, 0.0134577, 0.0234555
], [c.raw_score for c in contact_map1])
os.unlink(f_name)
def test_write_5(self):
contact_file = ContactFile('RR')
contact_map = ContactMap('1')
contact_file.add(contact_map)
for c in [(1, 9, 0, 8, 1.5), (1, 10, 0, 8, -0.3), (2, 8, 0, 8, 0.9),
(3, 12, 0, 8, 0.4)]:
contact = Contact(c[0], c[1], c[4], distance_bound=(c[2], c[3]))
contact_map.add(contact)
contact_map.sequence = Sequence(
'1',
'HLEGSIGILLKKHEIVFDGCHDFGRTYIWQMSDHLEGSIGILLKKHEIVFDGCHDFGRTYIWQMSD'
)
f_name = create_tmp_f()
with open(f_name, 'w') as f_out:
CaspParser().write(f_out, contact_file)
content = [
"PFRMAT RR",
"MODEL 1",
"HLEGSIGILLKKHEIVFDGCHDFGRTYIWQMSDHLEGSIGILLKKHEIVF",
"DGCHDFGRTYIWQMSD",
"1 9 0 8 1.000000",
"1 10 0 8 0.000000",
"2 8 0 8 0.666667",
"3 12 0 8 0.388889",
"ENDMDL",
"END",
]
with open(f_name, 'r') as f_in:
output = f_in.read().splitlines()
self.assertEqual(content, output)
os.unlink(f_name)
def test_write_4(self):
contact_file = ContactFile('RR')
contact_map = ContactMap('1')
contact_file.add(contact_map)
for c in [(1, 9, 0, 8, 0.7), (1, 10, 0, 8, 0.7), (2, 8, 0, 8, 0.9),
(3, 12, 0, 8, 0.4)]:
contact = Contact(c[0], c[1], c[4], distance_bound=(c[2], c[3]))
contact_map.add(contact)
contact_map.sequence = Sequence(
'1',
'HLEGSIGILLKKHEIVFDGCHDFGRTYIWQMSDHLEGSIGILLKKHEIVFDGCHDFGRTYIWQMSD'
)
f_name = create_tmp_f()
with open(f_name, 'w') as f_out:
CaspParser().write(f_out, contact_file)
content = [
"PFRMAT RR",
"MODEL 1",
"HLEGSIGILLKKHEIVFDGCHDFGRTYIWQMSDHLEGSIGILLKKHEIVF",
"DGCHDFGRTYIWQMSD",
"1 9 0 8 0.700000",
"1 10 0 8 0.700000",
"2 8 0 8 0.900000",
"3 12 0 8 0.400000",
"ENDMDL",
"END",
"",
]
content = os.linesep.join(content)
with open(f_name, 'r') as f_in:
data = "".join(f_in.readlines())
self.assertEqual(content, data)
os.unlink(f_name)
def test_read_2(self):
content = """PFRMAT RR
TARGET R9999
AUTHOR 1234-5678-9000
REMARK Predictor remarks
METHOD Description of methods used
MODEL 1
1 9 0 8 0.70
1 10 0 8 0.70
1 12 0 8 0.60
2 8 0 8 0.90
3 7 0 8 0.70
3 12 0 8 0.40
4 6 0 8 0.90
7 14 0 8 0.30
9 14 0 8 0.50
END
"""
f_name = create_tmp_f(content=content)
with open(f_name, 'r') as f_in:
contact_file = CaspParser().read(f_in)
contact_map1 = contact_file.top_map
self.assertEqual(1, len(contact_file))
self.assertEqual(9, len(contact_map1))
self.assertIsNone(contact_map1.sequence)
with self.assertRaises(TypeError):
_ = contact_map1.repr_sequence
os.unlink(f_name)
def test_read_3(self):
content = """#identifier diversity direction viterbiscore indexpred state res1 res2
1EAZ 0.65 Antiparallel 9.860725 1 first 29 24
1EAZ 0.65 Antiparallel 9.860725 1 internal 30 23
1EAZ 0.65 Antiparallel 9.860725 1 last 31 22
1EAZ 0.65 Parallel -6.855870 29 first 87 54
1EAZ 0.65 Parallel -6.855870 29 internal 88 55
1EAZ 0.65 Parallel -6.855870 29 last 89 56
1EAZ 0.65 Antiparallel 0.000000 1 first 100 24
1EAZ 0.65 Antiparallel 0.000000 1 last 101 23
1EAZ 0.65 Parallel 0.000000 29 first 100 15
"""
f_name = create_tmp_f(content=content)
with open(f_name, 'r') as f_in:
contact_file = BbcontactsParser().read(f_in, del_one_two=False)
contact_map1 = contact_file.top_map
self.assertEqual(1, len(contact_file))
self.assertEqual(9, len(contact_map1))
self.assertEqual([24, 23, 22, 54, 55, 56, 24, 23, 15],
[c.res1_seq for c in contact_map1])
self.assertEqual([29, 30, 31, 87, 88, 89, 100, 101, 100],
[c.res2_seq for c in contact_map1])
self.assertEqual(
sorted([
9.860725, 9.860725, 9.860725, -6.855870, -6.855870, -6.855870,
0.0, 0.0, 0.0
]), sorted([c.raw_score for c in contact_map1]))
os.unlink(f_name)
def test_write_1(self):
msa = [
'GSMFTPKPPQDSAVI--GYCVKQGAVMKNWKRRY--LDENTIGYF',
'EVHK--ECKQSDIMMRD--FEIVTTSRTFYVQADSPEEMHSWIKA',
'EVHKVQECK--DIMMRDNLFEI--TSRTFWKRRY--LDENTIGYF',
'EVHKVQECK--DIMMRDNLFEI--TSRTF--RRY--LDENTIGYF',
]
f_name_in = create_tmp_f(content='\n'.join(msa))
f_name_out = create_tmp_f()
parser = A2mParser()
with open(f_name_in, 'r') as f_in, open(f_name_out, 'w') as f_out:
sequence_file = parser.read(f_in)
parser.write(f_out, sequence_file)
with open(f_name_out, 'r') as f_in:
output = f_in.read().splitlines()
self.assertEqual(msa, output)
map(os.unlink, [f_name_in, f_name_out])
def test_create_tmp_f_2(self):
content = 'Hello, World!'
fname = _iotools.create_tmp_f(content=content, mode='w')
self.assertTrue(os.path.isfile(fname))
with open(fname, 'r') as f_in:
written_content = f_in.read()
self.assertEqual(content, written_content)
os.unlink(fname)
def test_write_1(self):
seq = [
">00FAF_A|<unknown description>",
"GSMFTPKPPQDSAVIKAGYCVKQGAVMKNWKRRYFQLDENTIGYFKSELEKEPLRVIPLK",
"EVHKVQECKQSDIMMRDNLFEIVTTSRTFYVQADSPEEMHSWIKAVSGAIVAQRGPGRSA",
"SSEHP",
]
f_name_in = create_tmp_f(content='\n'.join(seq))
f_name_out = create_tmp_f()
parser = FastaParser()
with open(f_name_in, 'r') as f_in, open(f_name_out, 'w') as f_out:
sequence_file = parser.read(f_in)
parser.write(f_out, sequence_file)
with open(f_name_out, 'r') as f_in:
output = f_in.read().splitlines()
self.assertEqual(seq, output)
map(os.unlink, [f_name_in, f_name_out])
def test_read_4(self):
content = """ATOM 1 N TYR A 36 39.107 51.628 3.103 0.50 43.13 N
ATOM 2 CA TYR A 36 38.300 50.814 2.204 0.50 41.80 C
ATOM 3 O TYR A 36 38.712 48.587 1.405 0.50 41.03 O
ATOM 4 CB TYR A 36 37.586 51.694 1.175 0.50 41.61 C
ATOM 5 N PHE A 86 32.465 47.498 5.487 0.50 25.81 N
ATOM 6 CA PHE A 86 32.670 48.303 4.288 0.50 26.45 C
ATOM 7 O PHE A 86 31.469 50.326 3.758 0.50 28.47 O
ATOM 8 CB PHE A 86 32.977 47.392 3.090 0.50 25.35 C
TER
ATOM 9 N TRP B 171 23.397 37.507 -1.161 0.50 18.04 N
ATOM 10 CA TRP B 171 23.458 36.846 0.143 0.50 20.46 C
ATOM 11 O TRP B 171 22.235 34.954 0.951 0.50 22.45 O
ATOM 12 CB TRP B 171 23.647 37.866 1.275 0.50 18.83 C
ATOM 13 N PHE B 208 32.221 42.624 -5.829 0.50 19.96 N
ATOM 14 CA PHE B 208 31.905 43.710 -4.909 0.50 20.31 C
ATOM 15 O PHE B 208 32.852 45.936 -5.051 0.50 17.69 O
ATOM 16 CB PHE B 208 31.726 43.102 -3.518 0.50 19.90 C
END
"""
f_name = create_tmp_f(content=content)
with open(f_name, 'r') as f_in:
contact_file = PdbParser().read(f_in,
distance_cutoff=8,
atom_type='CB')
# Two maps because no contacts in B
contact_map1 = contact_file['A'] # chain A
contact_map2 = contact_file['AB'] # chain AB
contact_map3 = contact_file['BA'] # chain BA
self.assertEqual(3, len(contact_file))
self.assertEqual(1, len(contact_map1))
self.assertEqual(['A', 'A'], [
contact_map1.top_contact.res1_chain,
contact_map1.top_contact.res2_chain
])
self.assertEqual([36, 86], [
contact_map1.top_contact.res1_seq,
contact_map1.top_contact.res2_seq
])
self.assertEqual(1, len(contact_map2))
self.assertEqual(['A', 'B'], [
contact_map2.top_contact.res1_chain,
contact_map2.top_contact.res2_chain
])
self.assertEqual([86, 208], [
contact_map2.top_contact.res1_seq,
contact_map2.top_contact.res2_seq
])
self.assertEqual(1, len(contact_map3))
self.assertEqual(['B', 'A'], [
contact_map3.top_contact.res1_chain,
contact_map3.top_contact.res2_chain
])
self.assertEqual([208, 86], [
contact_map3.top_contact.res1_seq,
contact_map3.top_contact.res2_seq
])
os.unlink(f_name)
def test_open_f_handle_4(self):
fname = _iotools.create_tmp_f()
with _iotools.open_f_handle(fname, 'write') as fhandle:
self.assertEqual('w', fhandle.mode)
fhandle.write("hello world!")
with _iotools.open_f_handle(fname, 'read') as fhandle:
self.assertEqual('r', fhandle.mode)
self.assertEqual("hello world!", fhandle.read().strip())
os.unlink(fname)