mgf - read and write MS/MS data in Mascot Generic Format¶
Summary¶
MGF is a simple human-readable format for MS/MS data. It allows storing MS/MS peak lists and exprimental parameters.
This module provides classes and functions for access to data stored in
MGF files.
Parsing is done using MGF
and IndexedMGF
classes.
The read()
function can be used as an entry point.
MGF spectra are converted to dictionaries. MS/MS data points are
(optionally) represented as numpy
arrays.
Also, common parameters can be read from MGF file header with
read_header()
function.
write()
allows creation of MGF files.
Classes¶
MGF
- a text-mode MGF parser. Suitable to read spectra from a file consecutively. Needs a file opened in text mode (or will open it if given a file name).
IndexedMGF
- a binary-mode MGF parser. When created, builds a byte offset index for fast random access by spectrum titles. Sequential iteration is also supported. Needs a seekable file opened in binary mode (if created from existing file object).
MGFBase
- abstract class, the common ancestor of the two classes above. Can be used for type checking.
Functions¶
read()
- an alias forMGF
orIndexedMGF
.
get_spectrum()
- read a single spectrum with given title from a file.
chain()
- read multiple files at once.
chain.from_iterable()
- read multiple files at once, using an iterable of files.
read_header()
- get a dict with common parameters for all spectra from the beginning of MGF file.
write()
- write an MGF file.
- pyteomics.mgf.chain(*args, **kwargs)¶
Chain
read()
for several files. Positional arguments should be file names or file objects. Keyword arguments are passed to theread()
function.
- chain.from_iterable(files, **kwargs)¶
Chain
read()
for several files. Keyword arguments are passed to theread()
function.- Parameters:
files (iterable) – Iterable of file names or file objects.
- class pyteomics.mgf.IndexedMGF(source=None, use_header=True, convert_arrays=2, read_charges=True, dtype=None, encoding='utf-8', index_by_scans=False, read_ions=False, _skip_index=False, **kwargs)[source]¶
Bases:
MGFBase
,TaskMappingMixin
,TimeOrderedIndexedReaderMixin
,IndexSavingTextReader
A class representing an MGF file. Supports the with syntax and direct iteration for sequential parsing. Specific spectra can be accessed by title using the indexing syntax in constant time. If created using a file object, it needs to be opened in binary mode.
When iterated,
IndexedMGF
object yields spectra one by one. Each ‘spectrum’ is adict
with five keys: ‘m/z array’, ‘intensity array’, ‘charge array’, ‘ion array’ and ‘params’. ‘m/z array’ and ‘intensity array’ storenumpy.ndarray
’s of floats, ‘charge array’ is a masked array (numpy.ma.MaskedArray
) of ints, ‘ion_array’ is an array of Ions (str) and ‘params’ stores adict
of parameters (keys and values arestr
, keys corresponding to MGF, lowercased).- time¶
A property used for accessing spectra by retention time.
- Type:
RTLocator
- __init__(source=None, use_header=True, convert_arrays=2, read_charges=True, dtype=None, encoding='utf-8', index_by_scans=False, read_ions=False, _skip_index=False, **kwargs)[source]¶
Create an
IndexedMGF
(binary-mode) reader for a given MGF file.- Parameters:
source (str or file or None, optional) –
A file object (or file name) with data in MGF format. Default is
None
, which means read standard input.Note
If a file object is given, it must be opened in binary mode.
use_header (bool, optional) – Add the info from file header to each dict. Spectrum-specific parameters override those from the header in case of conflict. Default is
True
.convert_arrays (one of {0, 1, 2}, optional) – If 0, m/z, intensities and (possibly) charges will be returned as regular lists. If 1, they will be converted to regular
numpy.ndarray
’s. If 2, charges will be reported as a masked array (default). The default option is the slowest. 1 and 2 requirenumpy
.read_charges (bool, optional) – If True (default), fragment charges are reported. Disabling it improves performance.
read_ions (bool, optional) – If True (default: False), fragment ion types are reported. Disabling it improves performance. Note that right now, only one of (read_charges, read_ions) may be True.
dtype (type or str or dict, optional) – dtype argument to
numpy
array constructor, one for all arrays or one for each key. Keys should be ‘m/z array’, ‘intensity array’, ‘charge array’ and/or ‘ion array’.encoding (str, optional) – File encoding.
block_size (int, optinal) – Size of the chunk (in bytes) used to parse the file when creating the byte offset index.
- Returns:
out – The reader object.
- Return type:
- map(target=None, processes=-1, args=None, kwargs=None, **_kwargs)¶
Execute the
target
function over entries of this object across up toprocesses
processes.Results will be returned out of order.
- Parameters:
target (
Callable
, optional) – The function to execute over each entry. It will be given a single object yielded by the wrapped iterator as well as all of the values inargs
andkwargs
processes (int, optional) – The number of worker processes to use. If 0 or negative, defaults to the number of available CPUs. This parameter can also be set at reader creation.
args (
Sequence
, optional) – Additional positional arguments to be passed to the target functionkwargs (
Mapping
, optional) – Additional keyword arguments to be passed to the target function**_kwargs – Additional keyword arguments to be passed to the target function
- Yields:
object – The work item returned by the target function.
- classmethod prebuild_byte_offset_file(path)¶
Construct a new XML reader, build its byte offset index and write it to file
- Parameters:
path (str) – The path to the file to parse
- reset()¶
Resets the iterator to its initial state.
- write_byte_offsets()¶
Write the byte offsets in
_offset_index
to the file at_byte_offset_filename
- class pyteomics.mgf.MGF(source=None, use_header=True, convert_arrays=2, read_charges=True, read_ions=False, dtype=None, encoding=None)[source]¶
Bases:
MGFBase
,FileReader
A class representing an MGF file. Supports the with syntax and direct iteration for sequential parsing. Specific spectra can be accessed by title using the indexing syntax (if the file is seekable), but it takes linear time to search through the file. Consider using
IndexedMGF
for constant-time access to spectra.MGF
object behaves as an iterator, yielding spectra one by one. Each ‘spectrum’ is adict
with five keys: ‘m/z array’, ‘intensity array’, ‘charge array’, ‘ion array’ and ‘params’. ‘m/z array’ and ‘intensity array’ storenumpy.ndarray
’s of floats, ‘charge array’ is a masked array (numpy.ma.MaskedArray
) of ints, ‘ion_array’ is a masked array of Ions (str) and ‘params’ stores adict
of parameters (keys and values arestr
, keys corresponding to MGF, lowercased).- __init__(source=None, use_header=True, convert_arrays=2, read_charges=True, read_ions=False, dtype=None, encoding=None)[source]¶
Create an
MGF
(text-mode) reader for a given MGF file.- Parameters:
source (str or file or None, optional) –
A file object (or file name) with data in MGF format. Default is
None
, which means read standard input...note :: If a file object is given, it must be opened in text mode.
use_header (bool, optional) – Add the info from file header to each dict. Spectrum-specific parameters override those from the header in case of conflict. Default is
True
.convert_arrays (one of {0, 1, 2}, optional) – If 0, m/z, intensities and (possibly) charges will be returned as regular lists. If 1, they will be converted to regular
numpy.ndarray
’s. If 2, charges will be reported as a masked array (default). The default option is the slowest. 1 and 2 requirenumpy
.read_charges (bool, optional) – If True (default), fragment charges are reported. Disabling it improves performance.
read_ions (bool, optional) – If True (default: False), fragment ion types are reported. Disabling it improves performance. Note that right now, only one of (read_charges, read_ions) may be True.
dtype (type or str or dict, optional) – dtype argument to
numpy
array constructor, one for all arrays or one for each key. Keys should be ‘m/z array’, ‘intensity array’, ‘charge array’ and/or ‘ion array’.encoding (str, optional) – File encoding.
- Returns:
out – The reader object.
- Return type:
- reset()¶
Resets the iterator to its initial state.
- class pyteomics.mgf.MGFBase(source=None, **kwargs)[source]¶
Bases:
MaskedArrayConversionMixin
Abstract mixin class representing an MGF file. Subclasses implement different approaches to parsing.
- __init__(source=None, **kwargs)[source]¶
Create an MGF file object, set MGF-specific parameters.
- Parameters:
source (str or file or None, optional) – A file object (or file name) with data in MGF format. Default is
None
, which means read standard input.use_header (bool, optional, keyword only) – Add the info from file header to each dict. Spectrum-specific parameters override those from the header in case of conflict. Default is
True
.convert_arrays (one of {0, 1, 2}, optional, keyword only) – If 0, m/z, intensities and (possibly) charges or (possibly) ions will be returned as regular lists. If 1, they will be converted to regular
numpy.ndarray
’s. If 2, charges will be reported as a masked array (default). The default option is the slowest. 1 and 2 requirenumpy
.read_charges (bool, optional, keyword only) – If True (default), fragment charges are reported. Disabling it improves performance.
read_ions (bool, optional) – If True (default: False), fragment ions are reported. Disabling it improves performance. Note that right now, only one of (read_charges, read_ions) may be True.
dtype (type or str or dict, optional, keyword only) – dtype argument to
numpy
array constructor, one for all arrays or one for each key. Keys should be ‘m/z array’, ‘intensity array’, ‘charge array’ and/or ‘ion array’.encoding (str, optional, keyword only) – File encoding.
- pyteomics.mgf.get_spectrum(source, title, *args, **kwargs)[source]¶
Read one spectrum (with given title) from source.
See
read()
for explanation of parameters affecting the output.Note
Only the key-value pairs after the “TITLE =” line will be included in the output.
- pyteomics.mgf.read(*args, **kwargs)[source]¶
Returns a reader for a given MGF file. Most of the parameters repeat the instantiation signature of
MGF
andIndexedMGF
. Additional parameter use_index helps decide which class to instantiate for given source.- Parameters:
source (str or file or None, optional) – A file object (or file name) with data in MGF format. Default is
None
, which means read standard input.use_header (bool, optional) – Add the info from file header to each dict. Spectrum-specific parameters override those from the header in case of conflict. Default is
True
.convert_arrays (one of {0, 1, 2}, optional) – If 0, m/z, intensities and (possibly) charges will be returned as regular lists. If 1, they will be converted to regular
numpy.ndarray
’s. If 2, charges will be reported as a masked array (default). The default option is the slowest. 1 and 2 requirenumpy
.read_charges (bool, optional) – If True (default), fragment charges are reported. Disabling it improves performance.
read_ions (bool, optional) – If True (default: False), fragment ion types are reported. Disabling it improves performance. Note that right now, only one of (read_charges, read_ions) may be True.
dtype (type or str or dict, optional) – dtype argument to
numpy
array constructor, one for all arrays or one for each key. Keys should be ‘m/z array’, ‘intensity array’, ‘charge array’ and/or ‘ion array’.encoding (str, optional) – File encoding.
use_index (bool, optional) –
Determines which parsing method to use. If
True
(default), an instance ofIndexedMGF
is created. This facilitates random access by spectrum titles. If an open file is passed as source, it needs to be open in binary mode.If
False
, an instance ofMGF
is created. It reads source in text mode and is suitable for iterative parsing. Access by spectrum title requires linear search and thus takes linear time.block_size (int, optinal) – Size of the chunk (in bytes) used to parse the file when creating the byte offset index. (Accepted only for
IndexedMGF
.)
- Returns:
out – Instance of
MGF
orIndexedMGF
.- Return type:
- pyteomics.mgf.read_header(source)[source]¶
Read the specified MGF file, get search parameters specified in the header as a
dict
, the keys corresponding to MGF format (lowercased).
- pyteomics.mgf.write(spectra, output=None, header='', key_order=['title', 'pepmass', 'rtinseconds', 'charge'], fragment_format=None, write_charges=True, write_ions=False, use_numpy=None, param_formatters={'charge': <function _charge_repr>, 'pepmass': <function _pepmass_repr>})[source]¶
Create a file in MGF format.
- Parameters:
spectra (iterable) –
A sequence of dictionaries with keys ‘m/z array’, ‘intensity array’, and ‘params’. ‘m/z array’ and ‘intensity array’ should be sequences of
int
,float
, orstr
. Strings will be written ‘as is’. The sequences should be of equal length, otherwise excessive values will be ignored.’params’ should be a
dict
with keys corresponding to MGF format. Keys must be strings, they will be uppercased and used as is, without any format consistency tests. Values can be of any type allowing string representation.’charge array’ or ‘ion array’ can also be specified.
Note
Passing a single spectrum will work, but will trigger a warning. This usage pattern is discouraged. To ensure correct output when writing multiple spectra, it is recommended to construct a sequence of spectra first and then call
write()
once.See also
This discussion of usage patterns of
write()
: https://github.com/levitsky/pyteomics/discussions/109output (str or file or None, optional) –
Path or a file-like object open for writing. If an existing file is specified by file name, it will be opened for writing. Default value is
None
, which means using standard output.Note
The default mode for output files specified by name has been changed from a to w in pyteomics 4.6. See file_mode to override the mode.
header (dict or (multiline) str or list of str, optional) – In case of a single string or a list of strings, the header will be written ‘as is’. In case of dict, the keys (must be strings) will be uppercased.
write_charges (bool, optional) – If
False
, fragment charges from ‘charge array’ will not be written. Default isTrue
.write_ions (bool, optional) – If
False
, fragment ions from ‘ion array’ will not be written. IfTrue
, then write_charges is set toFalse
. Default isFalse
.fragment_format (str, optional) –
Format string for m/z, intensity and charge (or ion annotation) of a fragment. Useful to set the number of decimal places, e.g.:
fragment_format='%.4f %.0f'
. Default is'{} {} {}'
.Note
The supported format syntax differs depending on other parameters. If use_numpy is
True
andnumpy
is available, fragment peaks will be written usingnumpy.savetxt()
. Then, fragment_format must be recognized by that function.Otherwise, plain Python string formatting is done. See the docs for details on writing the format string. If some or all charges are missing, an empty string is substituted instead, so formatting as
float
orint
will raise an exception. Hence it is safer to just use{}
for charges.key_order (list, optional) –
A list of strings specifying the order in which params will be written in the spectrum header. Unlisted keys will be in arbitrary order. Default is
_default_key_order
.Note
This does not affect the order of lines in the global header.
param_formatters (dict, optional) – A dict mapping parameter names to functions. Each function must accept two arguments (key and value) and return a string. Default is
_default_value_formatters
.use_numpy (bool, optional) –
Controls whether fragment peak arrays are written using
numpy.savetxt()
. Usingnumpy.savetxt()
is faster, but cannot handle sparse arrays of fragment charges. You may want to disable this if you need to save spectra with ‘charge arrays’ with missing values.If not specified, will be set to the opposite of write_chrages. If
numpy
is not available, this parameter has no effect.file_mode (str, keyword only, optional) –
If output is a file name, defines the mode the file will be opened in. Otherwise will be ignored. Default is ‘w’.
Note
The default changed from ‘a’ in pyteomics 4.6.
encoding (str, keyword only, optional) – Output file encoding (if output is specified by name).
- Returns:
output
- Return type:
file