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Source code for galaxy.datatypes.molecules
# -*- coding: utf-8 -*-
import logging
import os
import subprocess
from galaxy.datatypes import (
data,
metadata
)
from galaxy.datatypes.binary import Binary
from galaxy.datatypes.data import get_file_peek
from galaxy.datatypes.metadata import MetadataElement
from galaxy.datatypes.sniff import (
get_headers,
iter_headers
)
from galaxy.datatypes.tabular import Tabular
from galaxy.datatypes.xml import GenericXml
log = logging.getLogger(__name__)
[docs]def count_special_lines(word, filename, invert=False):
"""
searching for special 'words' using the grep tool
grep is used to speed up the searching and counting
The number of hits is returned.
"""
try:
cmd = ["grep", "-c"]
if invert:
cmd.append('-v')
cmd.extend([word, filename])
out = subprocess.Popen(cmd, stdout=subprocess.PIPE)
return int(out.communicate()[0].split()[0])
except Exception:
pass
return 0
[docs]def count_lines(filename, non_empty=False):
"""
counting the number of lines from the 'filename' file
"""
try:
if non_empty:
out = subprocess.Popen(['grep', '-cve', '^\s*$', filename], stdout=subprocess.PIPE)
else:
out = subprocess.Popen(['wc', '-l', filename], stdout=subprocess.PIPE)
return int(out.communicate()[0].split()[0])
except Exception:
pass
return 0
[docs]class GenericMolFile(data.Text):
"""
Abstract class for most of the molecule files.
"""
MetadataElement(name="number_of_molecules", default=0, desc="Number of molecules", readonly=True, visible=True, optional=True, no_value=0)
[docs] def set_peek(self, dataset, is_multi_byte=False):
if not dataset.dataset.purged:
if (dataset.metadata.number_of_molecules == 1):
dataset.blurb = "1 molecule"
else:
dataset.blurb = "%s molecules" % dataset.metadata.number_of_molecules
dataset.peek = get_file_peek(dataset.file_name)
else:
dataset.peek = 'file does not exist'
dataset.blurb = 'file purged from disk'
[docs]class MOL(GenericMolFile):
file_ext = "mol"
[docs] def set_meta(self, dataset, **kwd):
"""
Set the number molecules, in the case of MOL its always one.
"""
dataset.metadata.number_of_molecules = 1
[docs]class SDF(GenericMolFile):
file_ext = "sdf"
[docs] def sniff(self, filename):
"""
Try to guess if the file is a SDF2 file.
An SDfile (structure-data file) can contain multiple compounds.
Each compound starts with a block in V2000 or V3000 molfile format,
which ends with a line equal to 'M END'.
This is followed by a non-structural data block, which ends with a line
equal to '$$$$'.
>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('drugbank_drugs.sdf')
>>> SDF().sniff(fname)
True
>>> fname = get_test_fname('github88.v3k.sdf')
>>> SDF().sniff(fname)
True
>>> fname = get_test_fname('chebi_57262.v3k.mol')
>>> SDF().sniff(fname)
False
"""
m_end_found = False
limit = 10000
idx = 0
with open(filename) as in_file:
for line in in_file:
idx += 1
line = line.rstrip('\n\r')
if idx < 4:
continue
elif idx == 4:
if len(line) != 39 or not(line.endswith(' V2000') or
line.endswith(' V3000')):
return False
elif not m_end_found:
if line == 'M END':
m_end_found = True
elif line == '$$$$':
return True
if idx == limit:
break
return False
[docs] def set_meta(self, dataset, **kwd):
"""
Set the number of molecules in dataset.
"""
dataset.metadata.number_of_molecules = count_special_lines("^\$\$\$\$$", dataset.file_name)
[docs] def split(cls, input_datasets, subdir_generator_function, split_params):
"""
Split the input files by molecule records.
"""
if split_params is None:
return None
if len(input_datasets) > 1:
raise Exception("SD-file splitting does not support multiple files")
input_files = [ds.file_name for ds in input_datasets]
chunk_size = None
if split_params['split_mode'] == 'number_of_parts':
raise Exception('Split mode "%s" is currently not implemented for SD-files.' % split_params['split_mode'])
elif split_params['split_mode'] == 'to_size':
chunk_size = int(split_params['split_size'])
else:
raise Exception('Unsupported split mode %s' % split_params['split_mode'])
def _read_sdf_records(filename):
lines = []
with open(filename) as handle:
for line in handle:
lines.append(line)
if line.startswith("$$$$"):
yield lines
lines = []
def _write_part_sdf_file(accumulated_lines):
part_dir = subdir_generator_function()
part_path = os.path.join(part_dir, os.path.basename(input_files[0]))
part_file = open(part_path, 'w')
part_file.writelines(accumulated_lines)
part_file.close()
try:
sdf_records = _read_sdf_records(input_files[0])
sdf_lines_accumulated = []
for counter, sdf_record in enumerate(sdf_records, start=1):
sdf_lines_accumulated.extend(sdf_record)
if counter % chunk_size == 0:
_write_part_sdf_file(sdf_lines_accumulated)
sdf_lines_accumulated = []
if sdf_lines_accumulated:
_write_part_sdf_file(sdf_lines_accumulated)
except Exception as e:
log.error('Unable to split files: %s' % str(e))
raise
split = classmethod(split)
[docs]class MOL2(GenericMolFile):
file_ext = "mol2"
[docs] def sniff(self, filename):
"""
Try to guess if the file is a MOL2 file.
>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('drugbank_drugs.mol2')
>>> MOL2().sniff(fname)
True
>>> fname = get_test_fname('drugbank_drugs.cml')
>>> MOL2().sniff(fname)
False
"""
limit = 60
idx = 0
with open(filename) as in_file:
for line in in_file:
line = line.rstrip('\n\r')
if line == '@<TRIPOS>MOLECULE':
return True
idx += 1
if idx == limit:
break
return False
[docs] def set_meta(self, dataset, **kwd):
"""
Set the number of lines of data in dataset.
"""
dataset.metadata.number_of_molecules = count_special_lines("@<TRIPOS>MOLECULE", dataset.file_name)
[docs] def split(cls, input_datasets, subdir_generator_function, split_params):
"""
Split the input files by molecule records.
"""
if split_params is None:
return None
if len(input_datasets) > 1:
raise Exception("MOL2-file splitting does not support multiple files")
input_files = [ds.file_name for ds in input_datasets]
chunk_size = None
if split_params['split_mode'] == 'number_of_parts':
raise Exception('Split mode "%s" is currently not implemented for MOL2-files.' % split_params['split_mode'])
elif split_params['split_mode'] == 'to_size':
chunk_size = int(split_params['split_size'])
else:
raise Exception('Unsupported split mode %s' % split_params['split_mode'])
def _read_mol2_records(filename):
lines = []
start = True
with open(filename) as handle:
for line in handle:
if line.startswith("@<TRIPOS>MOLECULE"):
if start:
start = False
else:
yield lines
lines = []
lines.append(line)
def _write_part_mol2_file(accumulated_lines):
part_dir = subdir_generator_function()
part_path = os.path.join(part_dir, os.path.basename(input_files[0]))
part_file = open(part_path, 'w')
part_file.writelines(accumulated_lines)
part_file.close()
try:
mol2_records = _read_mol2_records(input_files[0])
mol2_lines_accumulated = []
for counter, mol2_record in enumerate(mol2_records, start=1):
mol2_lines_accumulated.extend(mol2_record)
if counter % chunk_size == 0:
_write_part_mol2_file(mol2_lines_accumulated)
mol2_lines_accumulated = []
if mol2_lines_accumulated:
_write_part_mol2_file(mol2_lines_accumulated)
except Exception as e:
log.error('Unable to split files: %s' % str(e))
raise
split = classmethod(split)
[docs]class FPS(GenericMolFile):
"""
chemfp fingerprint file: http://code.google.com/p/chem-fingerprints/wiki/FPS
"""
file_ext = "fps"
[docs] def sniff(self, filename):
"""
Try to guess if the file is a FPS file.
>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('q.fps')
>>> FPS().sniff(fname)
True
>>> fname = get_test_fname('drugbank_drugs.cml')
>>> FPS().sniff(fname)
False
"""
header = get_headers(filename, sep='\t', count=1)
if header[0][0].strip() == '#FPS1':
return True
else:
return False
[docs] def set_meta(self, dataset, **kwd):
"""
Set the number of lines of data in dataset.
"""
dataset.metadata.number_of_molecules = count_special_lines('^#', dataset.file_name, invert=True)
[docs] def split(cls, input_datasets, subdir_generator_function, split_params):
"""
Split the input files by fingerprint records.
"""
if split_params is None:
return None
if len(input_datasets) > 1:
raise Exception("FPS-file splitting does not support multiple files")
input_files = [ds.file_name for ds in input_datasets]
chunk_size = None
if split_params['split_mode'] == 'number_of_parts':
raise Exception('Split mode "%s" is currently not implemented for MOL2-files.' % split_params['split_mode'])
elif split_params['split_mode'] == 'to_size':
chunk_size = int(split_params['split_size'])
else:
raise Exception('Unsupported split mode %s' % split_params['split_mode'])
def _write_part_fingerprint_file(accumulated_lines):
part_dir = subdir_generator_function()
part_path = os.path.join(part_dir, os.path.basename(input_files[0]))
part_file = open(part_path, 'w')
part_file.writelines(accumulated_lines)
part_file.close()
try:
header_lines = []
lines_accumulated = []
fingerprint_counter = 0
for line in open(input_files[0]):
if not line.strip():
continue
if line.startswith('#'):
header_lines.append(line)
else:
fingerprint_counter += 1
lines_accumulated.append(line)
if fingerprint_counter != 0 and fingerprint_counter % chunk_size == 0:
_write_part_fingerprint_file(header_lines + lines_accumulated)
lines_accumulated = []
if lines_accumulated:
_write_part_fingerprint_file(header_lines + lines_accumulated)
except Exception as e:
log.error('Unable to split files: %s' % str(e))
raise
split = classmethod(split)
[docs] def merge(split_files, output_file):
"""
Merging fps files requires merging the header manually.
We take the header from the first file.
"""
if len(split_files) == 1:
# For one file only, use base class method (move/copy)
return data.Text.merge(split_files, output_file)
if not split_files:
raise ValueError("No fps files given, %r, to merge into %s"
% (split_files, output_file))
out = open(output_file, "w")
first = True
for filename in split_files:
with open(filename) as handle:
for line in handle:
if line.startswith('#'):
if first:
out.write(line)
else:
# line is no header and not a comment, we assume the first header is written to out and we set 'first' to False
first = False
out.write(line)
out.close()
merge = staticmethod(merge)
[docs]class OBFS(Binary):
"""OpenBabel Fastsearch format (fs)."""
file_ext = 'obfs'
composite_type = 'basic'
allow_datatype_change = False
MetadataElement(name="base_name", default='OpenBabel Fastsearch Index',
readonly=True, visible=True, optional=True,)
[docs] def __init__(self, **kwd):
"""
A Fastsearch Index consists of a binary file with the fingerprints
and a pointer the actual molecule file.
"""
Binary.__init__(self, **kwd)
self.add_composite_file('molecule.fs', is_binary=True,
description='OpenBabel Fastsearch Index')
self.add_composite_file('molecule.sdf', optional=True,
is_binary=False, description='Molecule File')
self.add_composite_file('molecule.smi', optional=True,
is_binary=False, description='Molecule File')
self.add_composite_file('molecule.inchi', optional=True,
is_binary=False, description='Molecule File')
self.add_composite_file('molecule.mol2', optional=True,
is_binary=False, description='Molecule File')
self.add_composite_file('molecule.cml', optional=True,
is_binary=False, description='Molecule File')
[docs] def set_peek(self, dataset, is_multi_byte=False):
"""Set the peek and blurb text."""
if not dataset.dataset.purged:
dataset.peek = "OpenBabel Fastsearch Index"
dataset.blurb = "OpenBabel Fastsearch Index"
else:
dataset.peek = "file does not exist"
dataset.blurb = "file purged from disk"
[docs] def display_peek(self, dataset):
"""Create HTML content, used for displaying peek."""
try:
return dataset.peek
except Exception:
return "OpenBabel Fastsearch Index"
[docs] def display_data(self, trans, data, preview=False, filename=None,
to_ext=None, **kwd):
"""Apparently an old display method, but still gets called.
This allows us to format the data shown in the central pane via the "eye" icon.
"""
return "This is a OpenBabel Fastsearch format. You can speed up your similarity and substructure search with it."
[docs] def get_mime(self):
"""Returns the mime type of the datatype (pretend it is text for peek)"""
return 'text/plain'
[docs] def merge(split_files, output_file, extra_merge_args):
"""Merging Fastsearch indices is not supported."""
raise NotImplementedError("Merging Fastsearch indices is not supported.")
[docs] def split(cls, input_datasets, subdir_generator_function, split_params):
"""Splitting Fastsearch indices is not supported."""
if split_params is None:
return None
raise NotImplementedError("Splitting Fastsearch indices is not possible.")
[docs]class DRF(GenericMolFile):
file_ext = "drf"
[docs] def set_meta(self, dataset, **kwd):
"""
Set the number of lines of data in dataset.
"""
dataset.metadata.number_of_molecules = count_special_lines('\"ligand id\"', dataset.file_name, invert=True)
[docs]class PHAR(GenericMolFile):
"""
Pharmacophore database format from silicos-it.
"""
file_ext = "phar"
[docs] def set_peek(self, dataset, is_multi_byte=False):
if not dataset.dataset.purged:
dataset.peek = get_file_peek(dataset.file_name)
dataset.blurb = "pharmacophore"
else:
dataset.peek = 'file does not exist'
dataset.blurb = 'file purged from disk'
[docs]class PDB(GenericMolFile):
"""
Protein Databank format.
http://www.wwpdb.org/documentation/format33/v3.3.html
"""
file_ext = "pdb"
[docs] def sniff(self, filename):
"""
Try to guess if the file is a PDB file.
>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('5e5z.pdb')
>>> PDB().sniff(fname)
True
>>> fname = get_test_fname('drugbank_drugs.cml')
>>> PDB().sniff(fname)
False
"""
headers = iter_headers(filename, sep=' ', count=300)
h = t = c = s = k = e = False
for line in headers:
section_name = line[0].strip()
if section_name == 'HEADER':
h = True
elif section_name == 'TITLE':
t = True
elif section_name == 'COMPND':
c = True
elif section_name == 'SOURCE':
s = True
elif section_name == 'KEYWDS':
k = True
elif section_name == 'EXPDTA':
e = True
if h * t * c * s * k * e:
return True
else:
return False
[docs] def set_peek(self, dataset, is_multi_byte=False):
if not dataset.dataset.purged:
atom_numbers = count_special_lines("^ATOM", dataset.file_name)
hetatm_numbers = count_special_lines("^HETATM", dataset.file_name)
dataset.peek = get_file_peek(dataset.file_name)
dataset.blurb = "%s atoms and %s HET-atoms" % (atom_numbers, hetatm_numbers)
else:
dataset.peek = 'file does not exist'
dataset.blurb = 'file purged from disk'
[docs]class PDBQT(GenericMolFile):
"""
PDBQT Autodock and Autodock Vina format
http://autodock.scripps.edu/faqs-help/faq/what-is-the-format-of-a-pdbqt-file
"""
file_ext = "pdbqt"
[docs] def sniff(self, filename):
"""
Try to guess if the file is a PDBQT file.
>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('NuBBE_1_obabel_3D.pdbqt')
>>> PDBQT().sniff(fname)
True
>>> fname = get_test_fname('drugbank_drugs.cml')
>>> PDBQT().sniff(fname)
False
"""
headers = iter_headers(filename, sep=' ', count=300)
h = t = c = s = k = False
for line in headers:
section_name = line[0].strip()
if section_name == 'REMARK':
h = True
elif section_name == 'ROOT':
t = True
elif section_name == 'ENDROOT':
c = True
elif section_name == 'BRANCH':
s = True
elif section_name == 'TORSDOF':
k = True
if h * t * c * s * k:
return True
else:
return False
[docs] def set_peek(self, dataset, is_multi_byte=False):
if not dataset.dataset.purged:
root_numbers = count_special_lines("^ROOT", dataset.file_name)
branch_numbers = count_special_lines("^BRANCH", dataset.file_name)
dataset.peek = get_file_peek(dataset.file_name)
dataset.blurb = "%s roots and %s branches" % (root_numbers, branch_numbers)
else:
dataset.peek = 'file does not exist'
dataset.blurb = 'file purged from disk'
[docs]class grd(data.Text):
file_ext = "grd"
[docs] def set_peek(self, dataset, is_multi_byte=False):
if not dataset.dataset.purged:
dataset.peek = get_file_peek(dataset.file_name)
dataset.blurb = "grids for docking"
else:
dataset.peek = 'file does not exist'
dataset.blurb = 'file purged from disk'
[docs]class grdtgz(Binary):
file_ext = "grd.tgz"
[docs] def set_peek(self, dataset, is_multi_byte=False):
if not dataset.dataset.purged:
dataset.peek = 'binary data'
dataset.blurb = "compressed grids for docking"
else:
dataset.peek = 'file does not exist'
dataset.blurb = 'file purged from disk'
[docs]class InChI(Tabular):
file_ext = "inchi"
column_names = ['InChI']
MetadataElement(name="columns", default=2, desc="Number of columns", readonly=True, visible=False)
MetadataElement(name="column_types", default=['str'], param=metadata.ColumnTypesParameter, desc="Column types", readonly=True, visible=False)
MetadataElement(name="number_of_molecules", default=0, desc="Number of molecules", readonly=True, visible=True, optional=True, no_value=0)
[docs] def set_meta(self, dataset, **kwd):
"""
Set the number of lines of data in dataset.
"""
dataset.metadata.number_of_molecules = self.count_data_lines(dataset)
[docs] def set_peek(self, dataset, is_multi_byte=False):
if not dataset.dataset.purged:
if (dataset.metadata.number_of_molecules == 1):
dataset.blurb = "1 molecule"
else:
dataset.blurb = "%s molecules" % dataset.metadata.number_of_molecules
dataset.peek = get_file_peek(dataset.file_name)
else:
dataset.peek = 'file does not exist'
dataset.blurb = 'file purged from disk'
[docs] def sniff(self, filename):
"""
Try to guess if the file is a InChI file.
>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('drugbank_drugs.inchi')
>>> InChI().sniff(fname)
True
>>> fname = get_test_fname('drugbank_drugs.cml')
>>> InChI().sniff(fname)
False
"""
inchi_lines = iter_headers(filename, sep=' ', count=10)
for inchi in inchi_lines:
if not inchi[0].startswith('InChI='):
return False
return True
[docs]class SMILES(Tabular):
file_ext = "smi"
column_names = ['SMILES', 'TITLE']
MetadataElement(name="columns", default=2, desc="Number of columns", readonly=True, visible=False)
MetadataElement(name="column_types", default=['str', 'str'], param=metadata.ColumnTypesParameter, desc="Column types", readonly=True, visible=False)
MetadataElement(name="number_of_molecules", default=0, desc="Number of molecules", readonly=True, visible=True, optional=True, no_value=0)
[docs] def set_meta(self, dataset, **kwd):
"""
Set the number of lines of data in dataset.
"""
dataset.metadata.number_of_molecules = self.count_data_lines(dataset)
[docs] def set_peek(self, dataset, is_multi_byte=False):
if not dataset.dataset.purged:
if dataset.metadata.number_of_molecules == 1:
dataset.blurb = "1 molecule"
else:
dataset.blurb = "%s molecules" % dataset.metadata.number_of_molecules
dataset.peek = get_file_peek(dataset.file_name)
else:
dataset.peek = 'file does not exist'
dataset.blurb = 'file purged from disk'
'''
def sniff(self, filename):
"""
Its hard or impossible to sniff a SMILES File. We can
try to import the first SMILES and check if it is a molecule, but
currently its not possible to use external libraries in datatype definition files.
Moreover it seems mpossible to inlcude OpenBabel as python library because OpenBabel
is GPL licensed.
"""
self.molecule_number = count_lines(filename, non_empty = True)
word_count = count_lines(filename)
if self.molecule_number != word_count:
return False
if self.molecule_number > 0:
# test first 3 SMILES
smiles_lines = get_headers(filename, sep='\t', count=3)
for smiles_line in smiles_lines:
if len(smiles_line) > 2:
return False
smiles = smiles_line[0]
try:
# if we have atoms, we have a molecule
if not len(pybel.readstring('smi', smiles).atoms) > 0:
return False
except Exception:
# if convert fails its not a smiles string
return False
return True
else:
return False
'''
[docs]class CML(GenericXml):
"""
Chemical Markup Language
http://cml.sourceforge.net/
"""
file_ext = "cml"
MetadataElement(name="number_of_molecules", default=0, desc="Number of molecules", readonly=True, visible=True, optional=True, no_value=0)
[docs] def set_meta(self, dataset, **kwd):
"""
Set the number of lines of data in dataset.
"""
dataset.metadata.number_of_molecules = count_special_lines('^\s*<molecule', dataset.file_name)
[docs] def set_peek(self, dataset, is_multi_byte=False):
if not dataset.dataset.purged:
if (dataset.metadata.number_of_molecules == 1):
dataset.blurb = "1 molecule"
else:
dataset.blurb = "%s molecules" % dataset.metadata.number_of_molecules
dataset.peek = get_file_peek(dataset.file_name)
else:
dataset.peek = 'file does not exist'
dataset.blurb = 'file purged from disk'
[docs] def sniff(self, filename):
"""
Try to guess if the file is a CML file.
>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('interval.interval')
>>> CML().sniff(fname)
False
>>> fname = get_test_fname('drugbank_drugs.cml')
>>> CML().sniff(fname)
True
"""
with open(filename) as handle:
line = handle.readline()
if line.strip() != '<?xml version="1.0"?>':
return False
line = handle.readline()
if line.strip().find('http://www.xml-cml.org/schema') == -1:
return False
return True
[docs] def split(cls, input_datasets, subdir_generator_function, split_params):
"""
Split the input files by molecule records.
"""
if split_params is None:
return None
if len(input_datasets) > 1:
raise Exception("CML-file splitting does not support multiple files")
input_files = [ds.file_name for ds in input_datasets]
chunk_size = None
if split_params['split_mode'] == 'number_of_parts':
raise Exception('Split mode "%s" is currently not implemented for CML-files.' % split_params['split_mode'])
elif split_params['split_mode'] == 'to_size':
chunk_size = int(split_params['split_size'])
else:
raise Exception('Unsupported split mode %s' % split_params['split_mode'])
def _read_cml_records(filename):
lines = []
with open(filename) as handle:
for line in handle:
if line.lstrip().startswith('<?xml version="1.0"?>') or \
line.lstrip().startswith('<cml xmlns="http://www.xml-cml.org/schema') or \
line.lstrip().startswith('</cml>'):
continue
lines.append(line)
if line.lstrip().startswith('</molecule>'):
yield lines
lines = []
header_lines = ['<?xml version="1.0"?>\n', '<cml xmlns="http://www.xml-cml.org/schema">\n']
footer_line = ['</cml>\n']
def _write_part_cml_file(accumulated_lines):
part_dir = subdir_generator_function()
part_path = os.path.join(part_dir, os.path.basename(input_files[0]))
part_file = open(part_path, 'w')
part_file.writelines(header_lines)
part_file.writelines(accumulated_lines)
part_file.writelines(footer_line)
part_file.close()
try:
cml_records = _read_cml_records(input_files[0])
cml_lines_accumulated = []
for counter, cml_record in enumerate(cml_records, start=1):
cml_lines_accumulated.extend(cml_record)
if counter % chunk_size == 0:
_write_part_cml_file(cml_lines_accumulated)
cml_lines_accumulated = []
if cml_lines_accumulated:
_write_part_cml_file(cml_lines_accumulated)
except Exception as e:
log.error('Unable to split files: %s' % str(e))
raise
split = classmethod(split)
[docs] def merge(split_files, output_file):
"""
Merging CML files.
"""
if len(split_files) == 1:
# For one file only, use base class method (move/copy)
return data.Text.merge(split_files, output_file)
if not split_files:
raise ValueError("Given no CML files, %r, to merge into %s"
% (split_files, output_file))
with open(output_file, "w") as out:
for filename in split_files:
with open(filename) as handle:
header = handle.readline()
if not header:
raise ValueError("CML file %s was empty" % filename)
if not header.lstrip().startswith('<?xml version="1.0"?>'):
out.write(header)
raise ValueError("%s is not a valid XML file!" % filename)
line = handle.readline()
header += line
if not line.lstrip().startswith('<cml xmlns="http://www.xml-cml.org/schema'):
out.write(header)
raise ValueError("%s is not a CML file!" % filename)
molecule_found = False
for line in handle.readlines():
# We found two required header lines, the next line should start with <molecule >
if line.lstrip().startswith('</cml>'):
continue
if line.lstrip().startswith('<molecule'):
molecule_found = True
if molecule_found:
out.write(line)
out.write("</cml>\n")
merge = staticmethod(merge)