def score_with_edstats_to_list(mtz_file, pdb_file, f_label=None):
"""Scores residues against density, then returns list"""
assert os.path.exists(
mtz_file), 'MTZ file for edstats does not exist! {!s}'.format(mtz_file)
assert os.path.exists(
pdb_file), 'PDB file for edstats does not exist! {!s}'.format(mtz_file)
# Create a file handle and path for the output
temp_handle, temp_path = tempfile.mkstemp(suffix='.table',
prefix='edstats_')
# Collate summary of MTZ file
m_summ = MtzSummary(mtz_file)
# Use column labels if given
if (f_label is not None) and (f_label
not in m_summ.summary['colheadings']):
raise Sorry(
'Selected f_label ({}) not found in mtz file ({}) -- mtz contains columns {}'
.format(f_label, mtz_file, m_summ.summary['colheadings']))
# else guess the labels in the mtzfile
else:
f_label = m_summ.label.f
# Check for f_label
if not f_label:
raise Sorry(
'No F label selected/found in mtz file: {!s} -- mtz contains columns {}'
.format(mtz_file, m_summ.summary['colheadings']))
# Run EDSTATS on the files
try:
# Initialise Command Manager to run edstats
command = CommandManager('edstats.pl')
command.add_command_line_arguments([
'-hklin', mtz_file, '-xyzin', pdb_file, '-output', temp_path,
'-noerror', '-flabel', f_label
])
command.set_timeout(timeout=600)
command.run()
# Read the output
with os.fdopen(temp_handle) as f:
output = f.read().strip().replace('\r\n',
'\n').replace('\r',
'\n').splitlines()
command.file_output = output
finally:
os.remove(temp_path)
# Process the output header
if output:
# Check header and then remove the first three columns
header = output.pop(0).split()
assert header[:3] == [
'RT', 'CI', 'RN'
], 'edstats output headers are not as expected! {!s}'.format(output)
num_fields = len(header)
header = header[3:]
else:
header = []
# List to be returned
outputdata = []
# Process the rest of the data
for line in output:
line = line.strip()
if not line:
continue
fields = line.split()
if len(fields) != num_fields:
raise ValueError(
"Error Parsing EDSTATS output: Header & Data rows have different numbers of fields"
)
# Get and process the residue information - TODO CI column can include alternate conformer?! TODO
residue, chain, resnum = fields[:3]
try:
resnum = int(resnum)
inscode = ' '
except ValueError:
inscode = resnum[-1:]
resnum = int(resnum[:-1])
# Remove the processed columns
fields = fields[3:]
# Process the other columns (changing n/a to None and value to int)
for i, x in enumerate(fields):
if x == 'n/a':
fields[i] = None
else:
try:
fields[i] = int(x)
except ValueError:
try:
fields[i] = float(x)
except ValueError:
pass
outputdata.append([(residue, chain, resnum, inscode), fields])
return outputdata, header, command
def score_with_edstats_to_list(mtz_file, pdb_file):
"""Scores residues against density, then returns list"""
assert os.path.exists(
mtz_file), 'MTZ FILE FOR EDSTATS DOES NOT EXIST! {!s}'.format(mtz_file)
assert os.path.exists(
pdb_file), 'PDB FILE FOR EDSTATS DOES NOT EXIST! {!s}'.format(mtz_file)
# Create a file handle and path for the output
temp_handle, temp_path = tempfile.mkstemp(suffix='.table',
prefix='edstats_')
# Find the labels in the mtzfile
file_obj = MtzSummary(mtz_file)
f_label = file_obj.label.f
if not f_label:
raise ReflectionException(
'MTZ Summary ERROR: No F Label Found in MTZ File: {!s}'.format(
mtz_file))
# Run EDSTATS on the files
try:
# Initialise Command Manager to run edstats
command = CommandManager('edstats.pl')
command.add_command_line_arguments([
'-hklin', mtz_file, '-xyzin', pdb_file, '-output', temp_path,
'-noerror', '-flabel', f_label
])
command.set_timeout(timeout=600)
command.run()
# Read the output
with os.fdopen(temp_handle) as f:
output = f.read().strip().replace('\r\n',
'\n').replace('\r',
'\n').splitlines()
command.file_output = output
finally:
os.remove(temp_path)
# Process the output header
if output:
header = output.pop(0).split()
assert header[:3] == [
'RT', 'CI', 'RN'
], 'EDSTATS OUTPUT HEADERS ARE NOT AS EXPECTED! {!s}'.format(output)
num_fields = len(header)
header = header[3:]
else:
header = []
# List to be returned
outputdata = []
# Process the rest of the data
for line in output:
line = line.strip()
if not line:
continue
fields = line.split()
if len(fields) != num_fields:
raise ValueError(
"Error Parsing EDSTATS output: Header & Data rows have different numbers of fields"
)
# Get and process the residue information
residue, chain, resnum = fields[:3]
try:
resnum = int(resnum)
inscode = ' '
except ValueError:
inscode = resnum[-1:]
resnum = int(resnum[:-1])
# Remove the processed columns
fields = fields[3:]
# Process the other columns (changing n/a to None and value to int)
for i, x in enumerate(fields):
if x == 'n/a':
fields[i] = None
else:
try:
fields[i] = int(x)
except ValueError:
fields[i] = float(x)
outputdata.append([(residue, chain, resnum, inscode), fields])
return outputdata, header, command
