thisisanshgupta/Pycode · Datasets at Hugging Face

text stringlengths 0 828
newInstance.__dict__.update(jsonobject)
newInstance.uniquePeptides = set(newInstance.uniquePeptides)
newInstance.sharedPeptides = set(newInstance.sharedPeptides)
return newInstance"
1982,"def save(self, path, compress=True):
""""""Writes the ``.proteins`` and ``.peptides`` entries to the hard disk
as a ``proteindb`` file.

.. note::
If ``.save()`` is called and no ``proteindb`` file is present in the
specified path a new files is generated, otherwise the old file is
replaced.

:param path: filedirectory to which the ``proteindb`` file is written.
The output file name is specified by ``self.info['name']``
:param compress: bool, True to use zip file compression
""""""
with aux.PartiallySafeReplace() as msr:
filename = self.info['name'] + '.proteindb'
filepath = aux.joinpath(path, filename)
with msr.open(filepath, mode='w+b') as openfile:
self._writeContainer(openfile, compress=compress)"
1983,"def _writeContainer(self, filelike, compress=True):
""""""Writes the ``.proteins`` and ``.peptides`` entries to the
``proteindb`` format. In addition it also dumps the ``self.info`` entry
to the zipfile with the filename ``info``. For details see
:func:`maspy.auxiliary.writeJsonZipfile()`

:param filelike: path to a file (str) or a file-like object
:param compress: bool, True to use zip file compression
""""""
aux.writeJsonZipfile(filelike, self.proteins, compress, 'w', 'proteins')
aux.writeJsonZipfile(filelike, self.peptides, compress, 'a', 'peptides')
zipcomp = zipfile.ZIP_DEFLATED if compress else zipfile.ZIP_STORED
with zipfile.ZipFile(filelike, 'a', allowZip64=True) as containerFile:
infodata = {key: value for key, value in
viewitems(self.info) if key != 'path'
}
containerFile.writestr('info', json.dumps(infodata, zipcomp))"
1984,"def load(cls, path, name):
""""""Imports the specified ``proteindb`` file from the hard disk.

:param path: filedirectory of the ``proteindb`` file
:param name: filename without the file extension "".proteindb""

.. note:: this generates rather large files, which actually take longer
to import than to newly generate. Maybe saving / loading should be
limited to the protein database whitout in silico digestion
information.
""""""

filepath = aux.joinpath(path, name + '.proteindb')
with zipfile.ZipFile(filepath, 'r', allowZip64=True) as containerZip:
#Convert the zipfile data into a str object, necessary since
#containerZip.read() returns a bytes object.
proteinsString = io.TextIOWrapper(containerZip.open('proteins'),
encoding='utf-8'
).read()
peptidesString = io.TextIOWrapper(containerZip.open('peptides'),
encoding='utf-8'
).read()
infoString = io.TextIOWrapper(containerZip.open('info'),
encoding='utf-8'
).read()
newInstance = cls()
newInstance.proteins = json.loads(proteinsString,
object_hook=ProteinSequence.jsonHook)
newInstance.peptides = json.loads(peptidesString,
object_hook=PeptideSequence.jsonHook)
newInstance.info.update(json.loads(infoString))
return newInstance"
1985,"def _calculateCoverageMasks(proteindb, peptidedb):
""""""Calcualte the sequence coverage masks for all proteindb elements.
Private method used by :class:`ProteinDatabase`.

A coverage mask is a numpy boolean array with the length of the protein
sequence. Each protein position that has been covered in at least one
peptide is set to True. Coverage masks are calculated for unique and for
shared peptides. Peptides are matched to proteins according to positions
derived by the digestion of the FASTA file.

Alternatively peptides could also be matched to proteins just by
sequence as it is done in :func:`pyteomics.parser.coverage`, but this is
not the case here.

:param proteindb: a dictionary containing :class:`ProteinSequence`
entries, for example ``ProteinDatabase.proteins``
:param proteindb: a dictionary containing :class:`PeptideSequence`
entries, for example ``ProteinDatabase.peptides``

Sets two attributes for each ``ProteinSequence`` entry:
``.coverageMaskUnique`` = coverage mask of unique peptides
``.coverageMaskShared`` = coverage mask of shared peptides
""""""
for proteinId, proteinEntry in viewitems(proteindb):
coverageMaskUnique = numpy.zeros(proteinEntry.length(), dtype='bool')
for peptide in proteinEntry.uniquePeptides:
startPos, endPos = peptidedb[peptide].proteinPositions[proteinId]
coverageMaskUnique[startPos-1:endPos] = True
coverageMaskShared = numpy.zeros(proteinEntry.length(), dtype='bool')

newInstance.__dict__.update(jsonobject)

newInstance.uniquePeptides = set(newInstance.uniquePeptides)

newInstance.sharedPeptides = set(newInstance.sharedPeptides)

return newInstance"

1982,"def save(self, path, compress=True):

""""""Writes the ``.proteins`` and ``.peptides`` entries to the hard disk

as a ``proteindb`` file.

.. note::

If ``.save()`` is called and no ``proteindb`` file is present in the

specified path a new files is generated, otherwise the old file is

replaced.

:param path: filedirectory to which the ``proteindb`` file is written.

The output file name is specified by ``self.info['name']``

:param compress: bool, True to use zip file compression

""""""

with aux.PartiallySafeReplace() as msr:

filename = self.info['name'] + '.proteindb'

filepath = aux.joinpath(path, filename)

with msr.open(filepath, mode='w+b') as openfile:

self._writeContainer(openfile, compress=compress)"

1983,"def _writeContainer(self, filelike, compress=True):

""""""Writes the ``.proteins`` and ``.peptides`` entries to the

``proteindb`` format. In addition it also dumps the ``self.info`` entry

to the zipfile with the filename ``info``. For details see

:func:`maspy.auxiliary.writeJsonZipfile()`

:param filelike: path to a file (str) or a file-like object

:param compress: bool, True to use zip file compression

""""""

aux.writeJsonZipfile(filelike, self.proteins, compress, 'w', 'proteins')

aux.writeJsonZipfile(filelike, self.peptides, compress, 'a', 'peptides')

zipcomp = zipfile.ZIP_DEFLATED if compress else zipfile.ZIP_STORED

with zipfile.ZipFile(filelike, 'a', allowZip64=True) as containerFile:

infodata = {key: value for key, value in

viewitems(self.info) if key != 'path'

}

containerFile.writestr('info', json.dumps(infodata, zipcomp))"

1984,"def load(cls, path, name):

""""""Imports the specified ``proteindb`` file from the hard disk.

:param path: filedirectory of the ``proteindb`` file

:param name: filename without the file extension "".proteindb""

.. note:: this generates rather large files, which actually take longer

to import than to newly generate. Maybe saving / loading should be

limited to the protein database whitout in silico digestion

information.

""""""

filepath = aux.joinpath(path, name + '.proteindb')

with zipfile.ZipFile(filepath, 'r', allowZip64=True) as containerZip:

#Convert the zipfile data into a str object, necessary since

#containerZip.read() returns a bytes object.

proteinsString = io.TextIOWrapper(containerZip.open('proteins'),

encoding='utf-8'

).read()

peptidesString = io.TextIOWrapper(containerZip.open('peptides'),

encoding='utf-8'

).read()

infoString = io.TextIOWrapper(containerZip.open('info'),

encoding='utf-8'

).read()

newInstance = cls()

newInstance.proteins = json.loads(proteinsString,

object_hook=ProteinSequence.jsonHook)

newInstance.peptides = json.loads(peptidesString,

object_hook=PeptideSequence.jsonHook)

newInstance.info.update(json.loads(infoString))

return newInstance"

1985,"def _calculateCoverageMasks(proteindb, peptidedb):

""""""Calcualte the sequence coverage masks for all proteindb elements.

Private method used by :class:`ProteinDatabase`.

A coverage mask is a numpy boolean array with the length of the protein

sequence. Each protein position that has been covered in at least one

peptide is set to True. Coverage masks are calculated for unique and for

shared peptides. Peptides are matched to proteins according to positions

derived by the digestion of the FASTA file.

Alternatively peptides could also be matched to proteins just by

sequence as it is done in :func:`pyteomics.parser.coverage`, but this is

not the case here.

:param proteindb: a dictionary containing :class:`ProteinSequence`

entries, for example ``ProteinDatabase.proteins``

:param proteindb: a dictionary containing :class:`PeptideSequence`

entries, for example ``ProteinDatabase.peptides``

Sets two attributes for each ``ProteinSequence`` entry:

``.coverageMaskUnique`` = coverage mask of unique peptides

``.coverageMaskShared`` = coverage mask of shared peptides

""""""

for proteinId, proteinEntry in viewitems(proteindb):

coverageMaskUnique = numpy.zeros(proteinEntry.length(), dtype='bool')

for peptide in proteinEntry.uniquePeptides:

startPos, endPos = peptidedb[peptide].proteinPositions[proteinId]

coverageMaskUnique[startPos-1:endPos] = True

coverageMaskShared = numpy.zeros(proteinEntry.length(), dtype='bool')