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 = self.tempfile()
with open(f_name, "w") as f_out:
MemBrainParser().write(f_out, contact_file)
content = [
"Helix Position Residue Helix Position Residue Probability",
"Hx 1 H Hx 9 L 0.700000",
"Hx 1 H Hx 10 L 0.700000",
"Hx 2 L Hx 8 I 0.900000",
"Hx 3 E Hx 12 K 0.400000",
]
with open(f_name, "r") as f_in:
output = f_in.read().splitlines()
self.assertEqual(content, output)
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:
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",
]
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.set_sequence_register()
f_name = self.tempfile()
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",
]
with open(f_name, "r") as f_in:
output = f_in.read().splitlines()
self.assertEqual(content, output)
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('sequence_1',
'HLEGSIGILLKKHEIVFDGCHDFGRTYIWQMSD')
contact_map.set_sequence_register()
f_name = create_tmp_f()
with open(f_name, 'w') as f_out:
PconsParser().write(f_out, contact_file)
content = [
"##############################################################################",
"PconsC3 result file",
"Generated using ConKit",
"##############################################################################",
"Sequence number: 1",
"Sequence name: sequence_1",
"Sequence length: 33 aa.",
"Sequence:",
"HLEGSIGILLKKHEIVFDGCHDFGRTYIWQMSD",
"",
"",
"Predicted contacts:",
"Res1 Res2 Score",
" 1 9 0.700000",
" 1 10 0.700000",
" 2 8 0.900000",
" 3 12 0.400000",
"",
"##############################################################################",
]
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("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 = self.tempfile()
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)
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 = self.tempfile()
with open(f_name, "w") as f_out:
CaspParser().write(f_out, contact_file)
content = [
"PFRMAT RR",
"TARGET R9999",
"AUTHOR 1234-5678-9000",
"REMARK Predictor remarks",
"METHOD Description of methods used",
"METHOD Description of methods used",
"MODEL 1",
"HLEGSIGILLKKHEIVFDGCHDFGRTYIWQMSD",
"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)
def read(self, f_handle, f_id="casp"):
"""Read a contact file into a :obj:`~conkit.core.contactfile.ContactFile` instance
Parameters
----------
f_handle
Open file handle [read permissions]
f_id : str, optional
Unique contact file identifier
Returns
-------
:obj:`~conkit.core.contactfile.ContactFile`
"""
lines = [l.strip() for l in f_handle.readlines()]
contact_file = ContactFile(f_id)
it = iter(lines)
while True:
try:
line = next(it)
except StopIteration:
break
if RE_PRFMAT.match(line):
continue
elif RE_TARGET.match(line):
contact_file.remark = RE_TARGET.match(line).group(1)
elif RE_AUTHOR.match(line):
contact_file.author = RE_AUTHOR.match(line).group(1)
elif RE_REMARK.match(line):
contact_file.remark = RE_REMARK.match(line).group(1)
elif RE_METHOD.match(line):
contact_file.method = RE_METHOD.match(line).group(1)
elif RE_MODEL.match(line):
contact_map = ContactMap(RE_MODEL.match(line).group(1))
seq_chunks = []
while True:
try:
line = next(it)
except StopIteration:
break
if not line:
break
if RE_ENDMDL.match(line):
break
elif RE_END.match(line):
break
elif RE_SEQ.match(line):
seq_chunks.append(line)
else:
res1_entry, res2_entry, lb, ub, raw_score = RE_SPLIT.split(
line)
# Split in case we have chain in inter-molecular scenarios
res1_split = RE_RES.split(res1_entry)
if len(res1_split) == 1:
res1_chain, res1_seq = "", res1_split[0]
elif len(res1_split) == 4:
res1_chain, res1_seq = res1_split[1], res1_split[2]
res2_split = RE_RES.split(res2_entry)
if len(res2_split) == 1:
res2_chain, res2_seq = "", res2_split[0]
elif len(res2_split) == 4:
res2_chain, res2_seq = res2_split[1], res2_split[2]
contact = Contact(int(res1_seq),
int(res2_seq),
float(raw_score),
distance_bound=(float(lb),
float(ub)))
contact.res1_chain = res1_chain
contact.res2_chain = res2_chain
contact.res1_altseq = int(res1_seq)
contact.res2_altseq = int(res2_seq)
contact_map.add(contact)
if seq_chunks:
seq = "".join(seq_chunks)
sequence = Sequence("seq_{}".format(contact_map.id), seq)
contact_map.sequence = sequence
contact_map.set_sequence_register()
contact_file.add(contact_map)
elif RE_END.match(line):
break
else:
raise ValueError(
"Unrecognized line type. Please report this issue")
return contact_file