:tocdepth: 3 .. currentmodule:: gwpy.table .. _gwpy-table-io: ################################################################################# Reading and writing :class:`~astropy.table.Table` and :class:`EventTable` objects ################################################################################# .. note:: This document complements the upstream Astropy documentation on reading/writing :class:`~astropy.table.Table` objects, please refer to :any:`astropy:read_write_tables`. Astropy provides an excellent :any:`unified input/output ` system for the `~astropy.table.Table` object, and GWpy extends upon that to include common gravitational-wave file types, as well as providing event-specific input/output registrations for event data. In the most general case you can read a table of data as follows: .. code-block:: python :name: gwpy-table-io-example :caption: Reading an `EventTable` from an ASCII file >>> from gwpy.table import EventTable >>> table = EventTable.read('mydata.txt') :meth:`EventTable.read` will attempt to automatically identify the file format based on the file extension and/or the contents of the file, however, the ``format`` keyword argument can be used to manually identify the input file-format. The :meth:`~EventTable.read` and :meth:`~EventTable.write` methods take different arguments and keywords based on the input/output file format, see :ref:`gwpy-table-io-formats` for details on reading/writing for each of the built-in formats. .. _gwpy-table-gwosc: ************************************ Accessing Open Data event catalogues ************************************ |GWOSCl| publishes the Gravitational-Wave Transient Event Catalogues (GWTCs), allowing public access to tables of gravitational wave events and their parameters. GWpy's :class:`EventTable` class comes with a :meth:`~EventTable.fetch_open_data` method that queries the GWOSC database to download data for the relevant catalogue. .. _gwpy-table-gwosc-query: ============== Simple queries ============== The simplest query just requires the catalogue name, and will return all parameters for all events in the catalogue: .. code-block:: python :name: gwpy-table-io-fetch_open_data :caption: Fetching the GWTC-2 catalogue using :meth:`EventTable.fetch_open_data` (output correct as of |today|) >>> from gwpy.table import EventTable >>> events = EventTable.fetch_open_data("GWTC-2") >>> print(events) name final_mass_source_lower ... mass_2_source_upper mass_1_source_upper ... ------------------ ----------------------- ... ------------------- ------------------- GW190408_181802-v1 -2.8 ... 3.3 5.1 GW190412-v3 -3.8 ... 1.6 4.7 GW190413_052954-v1 -9.2 ... 7.3 12.6 GW190413_134308-v1 -11.4 ... 11.7 13.5 GW190421_213856-v1 -8.7 ... 8.0 10.4 GW190424_180648-v1 -10.1 ... 7.6 11.1 GW190425-v2 None ... 0.3 0.6 GW190426_152155-v1 None ... 0.8 3.9 GW190503_185404-v1 -7.7 ... 7.7 9.2 GW190512_180714-v1 -3.5 ... 3.6 5.3 GW190513_205428-v1 -5.8 ... 7.7 9.5 GW190514_065416-v1 -10.4 ... 9.3 14.7 GW190517_055101-v1 -8.9 ... 7.0 11.7 GW190519_153544-v1 -13.8 ... 11.0 10.7 GW190521-v3 -22.4 ... 22.7 28.7 GW190521_074359-v1 -4.4 ... 5.4 5.9 GW190527_092055-v1 -9.3 ... 10.5 16.4 GW190602_175927-v1 -14.9 ... 14.3 15.7 GW190620_030421-v1 -12.1 ... 12.2 16.0 GW190630_185205-v1 -4.6 ... 5.2 6.9 GW190701_203306-v1 -8.9 ... 8.7 11.8 GW190706_222641-v1 -13.5 ... 14.6 14.6 GW190707_093326-v1 -1.3 ... 1.4 3.3 GW190708_232457-v1 -1.8 ... 2.0 4.7 GW190719_215514-v1 -10.2 ... 9.0 18.0 GW190720_000836-v1 -2.2 ... 2.3 6.7 GW190727_060333-v1 -7.5 ... 7.1 9.5 GW190728_064510-v1 -1.3 ... 1.7 7.2 GW190731_140936-v1 -10.8 ... 9.7 12.2 GW190803_022701-v1 -8.5 ... 7.8 10.6 GW190814-v2 -0.9 ... 0.08 1.1 GW190828_063405-v1 -4.3 ... 4.6 5.8 GW190828_065509-v1 -4.5 ... 3.6 7.0 GW190909_114149-v1 -16.8 ... 13.4 52.7 GW190910_112807-v1 -8.6 ... 6.3 7.6 GW190915_235702-v1 -6.0 ... 5.6 9.5 GW190924_021846-v1 -1.0 ... 1.4 7.0 GW190929_012149-v1 -25.3 ... 19.3 33.0 GW190930_133541-v1 -1.5 ... 1.7 12.4 The full list of available columns can be queried as follows: .. code-block:: python :name: gwpy-table-io-fetch_open_data-info :caption: Printing the columns of an `EventTable` (output correct as of |today|) >>> print(events.info) name dtype unit description -------------------------------- ------- ------- -------------------------------- name str18 final_mass_source_lower object final_mass_source_lower chirp_mass_source_lower float64 chirp_mass_source_lower total_mass_source_upper float64 total_mass_source_upper chirp_mass_lower float64 chirp_mass_lower ... .. adminition:: GWOSC catalogues For more details on the GWOSC catalogues, see https://www.gw-openscience.org/catalog/. .. _gwpy-table-gwosc-filter: ================ Filtered queries ================ The columns returned can be selected using the ``column`` keyword, and mathematical selection filters can be applied on-the-fly using the ``selection`` keyword: .. code-block:: python :name: gwpy-table-io-fetch_open_data-filtered :caption: Downloading a sub-set of a catalogue from GWOSC (output correct as of |today|) >>> t = EventTable.fetch_open_data( ... "GWTC-2", ... selection="mass_1_source < 4", ... columns=["name", "mass_1_source", "mass_2_source", "luminosity_distance"], ... ) >>> print(t) name mass_1_source mass_2_source luminosity_distance solMass solMass Mpc ----------- ------------- ------------- ------------------- GW190425-v2 2.0 1.4 160.0 .. admonition:: More on filtering an `EventTable` For more information on filtering, see :ref:`gwpy-table-filter`. .. _gwpy-table-io-formats: ********************* Built-in file formats ********************* GWpy extends the Astropy functionality with readers for the following file formats: - :ref:`gwpy-table-io-ligolw` - :ref:`gwpy-table-io-ascii-cwb` - :ref:`gwpy-table-io-root` - :ref:`gwpy-table-io-pycbc_live` - :ref:`gwpy-table-io-gwf` Each of the sub-sections below outlines how to read and write in these file formats, include the custom keyword arguments to pass to :meth:`EventTable.read` and :meth:`EventTable.write`. .. admonition:: Listing all available formats To list all available formats, consult the documentation for :meth:`EventTable.read`. ============================ Multi-processed file reading ============================ The :meth:`EventTable.read` method accepts the ``nproc`` keyword argument, allowing multi-processed reading of lists of files. This argument can be used with any file-format, not just those defined below, but is **not** backported to for use with :meth:`Table.read`. .. _gwpy-table-io-ligolw: =============== ``LIGO_LW`` XML =============== **Additional dependencies:** |python-ligo-lw|_ The LIGO Scientific Collaboration uses a custom scheme of XML in which to store tabular data, called ``LIGO_LW``. Complementing the scheme is a python library - |python-ligo-lw|_ - which allows users to read and write all of the different types of tabular data produced by gravitational-wave searches. Reading and writing tables in ``LIGO_LW`` XML format is supported with ``format='ligolw', tablename='`` where ```` can be any of the supported LSC table names (see :mod:`ligo.lw.lsctables`). Reading ------- When reading, the ``tablename`` keyword argument should be given to identify the table in the file, as follows: .. code-block:: python :name: gwpy-table-io-ligolw-tablename :caption: Reading an `EventTable` from ``LIGO_LW`` XML. >>> t = EventTable.read('H1-LDAS_STRAIN-968654552-10.xml.gz', tablename='sngl_burst') The result should be something similar to this: .. code-block:: python :name: gwpy-table-io-ligolw-output :caption: Result of reading an `EventTable` from ``LIGO_LW`` XML. >>> print(t) ifo peak_time peak_time_ns start_time ... confidence chisq chisq_dof bandwidth --- --------- ------------ ---------- ... ---------- ----- --------- --------- H1 968654557 783203126 968654557 ... 16.811825 0.0 512.0 256.0 H1 968654557 781250001 968654557 ... 16.816761 0.0 512.0 256.0 H1 968654557 779296876 968654557 ... 16.696106 0.0 512.0 256.0 H1 968654557 777343751 968654557 ... 16.739489 0.0 512.0 256.0 H1 968654557 775390626 968654557 ... 16.802326 0.0 512.0 256.0 H1 968654557 773437501 968654557 ... 16.30731 0.0 512.0 256.0 H1 968654557 771484376 968654557 ... 16.307253 0.0 512.0 256.0 H1 968654557 769531251 968654557 ... 16.35647 0.0 512.0 256.0 H1 968654557 767578126 968654557 ... 16.561176 0.0 512.0 256.0 H1 968654557 765625001 968654557 ... 16.393112 0.0 512.0 256.0 H1 968654557 763671876 968654557 ... 16.404041 0.0 512.0 256.0 H1 968654557 761718751 968654557 ... 16.405825 0.0 512.0 256.0 H1 968654557 759765626 968654557 ... 16.715092 0.0 512.0 256.0 H1 968654557 757812501 968654557 ... 17.512749 0.0 512.0 256.0 H1 968654557 755859376 968654557 ... 17.347675 0.0 512.0 256.0 H1 968654557 753906251 968654557 ... 17.077478 0.0 512.0 256.0 H1 968654557 751953126 968654557 ... 16.742907 0.0 512.0 256.0 ... ... ... ... ... ... ... ... ... H1 968654560 342773438 968654559 ... 11.029792 0.0 16.0 8.0 H1 968654559 280273438 968654558 ... 12.363036 0.0 16.0 8.0 H1 968654559 217773438 968654558 ... 13.985101 0.0 16.0 8.0 H1 968654559 155273438 968654558 ... 14.662391 0.0 16.0 8.0 H1 968654559 92773438 968654558 ... 15.864924 0.0 16.0 8.0 H1 968654559 30273438 968654558 ... 16.321821 0.0 16.0 8.0 H1 968654558 967773438 968654558 ... 16.975931 0.0 16.0 8.0 H1 968654558 905273438 968654558 ... 19.160393 0.0 16.0 8.0 H1 968654560 811523438 968654560 ... 11.270205 0.0 8.0 4.0 H1 968654560 686523438 968654560 ... 15.839205 0.0 8.0 4.0 H1 968654560 561523438 968654560 ... 15.944695 0.0 8.0 4.0 H1 968654560 436523438 968654559 ... 14.384432 0.0 8.0 4.0 H1 968654560 311523438 968654559 ... 14.465309 0.0 8.0 4.0 H1 968654560 186523438 968654559 ... 13.045853 0.0 8.0 4.0 H1 968654560 561523438 968654560 ... 11.636543 0.0 4.0 4.0 H1 968654560 436523438 968654560 ... 15.344837 0.0 4.0 4.0 H1 968654560 311523438 968654560 ... 11.367717 0.0 4.0 4.0 Length = 2052 rows .. admonition:: Single-table files The ``tablename`` keyword can be omitted if there is only a single table in the file. To restrict the columns returned in the new `EventTable`, use the `columns` keyword argument: .. code-block:: python :name: gwpy-table-io-ligolw-columns :caption: Reading specific columns into an `EventTable` from ``LIGO_LW`` XML. >>> t = EventTable.read( ... "H1-LDAS_STRAIN-968654552-10.xml.gz", ... tablename="sngl_burst", ... columns=["peak_time", "peak_time_ns", "snr", "peak_frequency"], ... ) Many LIGO_LW table objects (as defined in :mod:`ligo.lw.lsctables`) include utility functions to create new columns by combining others, e.g. to calculate the Q of a sine-Gaussian pulse from the duration and central frequency. These 'columns' can be requested directly, providing the :class:`ligo.lw.table.Table` representation of the data has a :meth:`get_` method for that name: .. code-block:: python :name: gwpy-table-io-ligolw-get-columns :caption: Reading ``get_`` columns into an `EventTable` from ``LIGO_LW`` XML. >>> t = EventTable.read( ... "H1-LDAS_STRAIN-968654552-10.xml.gz", ... tablename="sngl_burst", ... columns=["snr", "q", "duration", "central_freq"], ... ) .. note:: When reading a processed column in this manner, all required input columns for a processed column must be included in the `columns` keyword list. To exclude these columns from the returned data, use the ``ligolw_columns=`` keyword to specify the columns required to provide the output columns: .. code-block:: python >>> t = EventTable.read( ... "H1-LDAS_STRAIN-968654552-10.xml.gz", ... tablename="sngl_burst", ... columns=["snr", "q"], ... ligolw_columns=["snr", "duration", "central_freq"], ... ) By default, the returned `EventTable` uses the dtypes returned by the :mod:`ligol.lw` library, and functions therein, which often end up as `numpy.object_` arrays in the table. To force all columns to have real `numpy` data types, use the ``use_numpy_dtypes=True`` keyword, which will cast (known) custom object types to a standard `numpy.dtype`, e.g: .. code-block:: python :name: gwpy-table-io-ligo-lw-use_numpy_dtypes :caption: Example of using ``use_numpy_dtypes=True`` when reading an `EventTable` from ``LIGO_LW`` XML. >>> t = EventTable.read( ... "H1-LDAS_STRAIN-968654552-10.xml.gz", ... tablename="sngl_burst", ... columns=["peak"], ... ligolw_columns=["peak_time", "peak_time_ns"]) >>> print(type(t[0]["peak"])) >>> t = EventTable.read( ... "H1-LDAS_STRAIN-968654552-10.xml.gz", ... tablename="sngl_burst", ... columns=["peak"], ... ligolw_columns=["peak_time", "peak_time_ns"], ... use_numpy_dtypes=True) >>> print(type(t[0]["peak"])) Writing ------- A table can be written as follows: .. code-block:: python >>> t.write('new-table.xml', format='ligolw', tablename='sngl_burst') Because ``LIGO_LW`` isn't the only scheme of XML, the ``format`` keyword is required for all `Table.write()` operations. If the target file already exists, an :class:`~exceptions.IOError` will be raised, use ``overwrite=True`` to force a new file to be written. To write a table to an existing file, use ``append=True``: .. code-block:: python >>> t.write('new-table.xml', format='ligolw', tablename='sngl_burst', append=True) To replace an existing table of the given type in an existing file, while preserving other tables, use *both* ``append=True`` and ``overwrite=True``: .. code-block:: python >>> t.write('new-table.xml', format='ligolw', tablename='sngl_burst', append=True, overwrite=True) .. note:: The |python-ligo-lw| library reads and writes files using an updated version of the ``LIGO_LW`` format compared to :mod:`glue.ligolw` used to. GWpy should support both format versions natively when _reading_, but when _writing_ you may need to explicitly pass the ``ilwdchar_compat=True`` keyword in order to write using the old format:: >>> t.write('new-table.xml', format='ligolw', tablename='sngl_burst', ... ilwdchar_compat=True) .. _gwpy-table-io-ascii-cwb: ============================================ Coherence WaveBurst ASCII (aka `EVENTS.txt`) ============================================ |cWBl|_ is an analysis pipeline is used to detect generic gravitational-wave bursts, without using a signal model to restrict the analysis, and runs in both low-latency (online) and offline modes over current GWO data. The analysis uses the ROOT framework for most data products, but also produces ASCII data in a custom format commonly written in a file called ``EVENTS.txt``. Reading ------- To read a cWB ASCII file: .. code-block:: python :name: gwpy-table-io-cwb-read :caption: Reading an `EventTable` from cWB-format ASCII. >>> t = EventTable.read('EVENTS.txt', format='ascii.cwb') See the :func:`astropy.io.ascii.read` documentation for full details on keyword arguments when reading ``ascii.cwb`` files. Writing ------- To write a table using the cWB ASCII format: .. code-block:: python :name: gwpy-table-io-cwb-write :caption: Writing an `EventTable` to a cWB-format ASCII file. >>> t.write('EVENTS.txt', format='ascii.cwb') [the output file name is not required to be ``'EVENTS.txt'``, this is simply the convention used in the cWB analysis.] .. _gwpy-table-io-root: ==== ROOT ==== **Additional dependencies:** |uproot|_ .. note:: |uproot|_ version 4 (at time of writing) cannot handle writing ROOT files, so if wish to use this version to read files, you may need to also install |uproot3|_ as well. Reading ------- To read a `ROOT `_ tree into a `Table` (or `EventTable`), specify the relevant tree via the ``treename`` keyword argument: .. code-block:: python :name: gwpy-table-io-root-read :caption: Reading an `EventTable` from a ROOT file. >>> t = Table.read('my-data.root', treename='triggers') If ``treename=None`` is given (default), a single tree will be read if only one exists in the file, otherwise a `ValueError` will be raised. Any other keyword arguments will be passed directly to :meth:`uproot.tree.TTreeMethods.arrays`. Writing ------- To write a `Table` as a ROOT tree: .. code-block:: python :name: gwpy-table-io-root-write :caption: Writing an `EventTable` to a ROOT file. >>> t.write('new-table.root') As with reading, the ``treename`` keyword argument can be used to specify the tree, the default is ``treename='tree'``. By default, an existing file with an existing tree of the given name will be appended to, to overwrite use the ``mode='recreate'`` keyword argument: .. code-block:: python :name: gwpy-table-io-root-write-mode :caption: Writing an `EventTable` over an existing tree in a ROOT file. >>> t.write('new-table.root', treename='triggers', mode='recreate') Any other keyword arguments will be passed directly to :class:`uproot.newtree`. .. _gwpy-table-io-pycbc_live: ================= PyCBC Live (HDF5) ================= PyCBC Live is a low-latency search for gravitational waves from compact binary coalescences, built from the |pycbc|_ analysis package. This search writes files on the LIGO Data Grid (LIGO.ORG-authenticated users only) in HDF5 format, containing tables of events; each column in the table is recorded as a separate HDF5 Dataset. Reading ------- To read an `EventTable` from a ``pycbc_live`` format HDF5 file, use the ``format='hdf5.pycbc_live'`` keyword: .. code-block:: python :name: gwpy-table-io-pycbc_live-read :caption: Reading an `EventTable` from a PyCBC-Live HDF5 file. >>> t = EventTable.read("H1-Live-1234567890-4.hdf", format="hdf5.pycbc_live") To restrict the returned columns, use the ``columns`` keyword argument: .. code-block:: python :name: gwpy-table-io-pycbc_live-read-columns :caption: Reading specific columns into an `EventTable` from PyCBC-Live HDF5. >>> t = EventTable.read( ... "H1-Live-1234567890-4.hdf", ... format="hdf5.pycbc_live", ... columns=["end_time", "snr", "chisq"], ... ) Similarly to the :ref:`gwpy-table-io-ligolw` format, some processed columns can be specified that are not included in the HDF5 files, but are created on-the-fly. Supported processed columns are: - ``mchirp`` - ``new_snr`` These can be specified without having to specify any of the input columns. Additionally, PyCBC HDF5 table Groups include extra datasets that aren't part of the table, e.g. ``'psd'``. These can be included in the returned `EventTable.meta` `dict` via the keyword ``extended_metadata=True`` (default), or excluded with ``extended_metadata=False``. Writing ------- Writing tables in PyCBC Live HDF5 format is not supported at this time. .. _gwpy-table-io-snax: =========== SNAX (HDF5) =========== The SNAX (Signal-based Noise Acquisition and eXtraction) analysis pipeline is a low-latency search for identifying glitches in h(t) and auxiliary channel data using glitch waveforms, operating in low-latency (online) and offline modes. This search writes files on the LIGO Data Grid (LIGO.ORG-authenticated users only) in HDF5 format containing regularly-sampled features; each channel in the table is recorded as a separate HDF5 Dataset. Reading ------- To read an `EventTable` from a ``snax`` format HDF5 file, use the ``format='hdf5.snax'`` keyword: .. code-block:: python :name: gwpy-table-io-snax-read :caption: Reading an `EventTable` from a SNAX-format HDF5 file. >>> t = EventTable.read("H-SNAX_FEATURES-1255853400-20.h5", format="hdf5.snax") By default, all channels contained in the file are read in. To restrict the returned channels, use the ``channels`` keyword argument: .. code-block:: python :name: gwpy-table-io-snax-read-channels :caption: Reading specific channels into an `EventTable` from a SNAX-format HDF5 file. >>> t = EventTable.read( ... "H-SNAX_FEATURES-1255853400-20.h5", ... format="hdf5.snax", ... channels="H1:CAL-DELTAL_EXTERNAL_DQ", ... ) To restrict the returned columns, use the ``columns`` keyword argument: .. code-block:: python :name: gwpy-table-io-snax-read :caption: Reading specific columns into an `EventTable` from SNAX-format HDF5. >>> t = EventTable.read( ... "H-GSTLAL_IDQ_FEATURES-1255853400-20.h5", ... format="hdf5.snax", ... columns=["channel", "time", "snr"], ... ) Writing ------- Writing tables in SNAX HDF5 format is not supported at this time. .. _gwpy-table-io-gwf: === GWF === **Additional dependencies:** |LDAStools.frameCPP|_ The Gravitational-Wave Frame file format supports tabular data via ``FrEvent`` structures, which allow storage of arbitrary event information. Reading ------- To read an `EventTable` from a ``GWF``-format file, specify the filename and the ``name`` of the ``FrEvent`` structures to read: .. code-block:: python :name: gwpy-table-io-gwf-read :caption: Reading an `EventTable` from GWF. >>> t = EventTable.read('events.gwf', 'my-event-name') To restrict the returned columns, use the ``columns`` keyword argument: .. code-block:: python :name: gwpy-table-io-gwf-read-columns :caption: Reading specific columns into an `EventTable` from GWF. >>> t = EventTable.read('events.gwf', 'my-event-name', columns=['time', 'amplitude']) All ``FrEvent`` structures contain the following columns, any other columns are use-specific: =============== ==================================================================================== Column name Description (from `LIGO-T970130 `_) =============== ==================================================================================== ``time`` Reference time of event, as defined by the search algorithm ``amplitude`` Continuous output amplitude returned by event ``probability`` Likelihood estimate of event, if available (probability = -1 if cannot be estimated) ``timeBefore`` Signal duration before reference time (seconds) ``timeAfter`` Signal duration after reference time (seconds) ``comment`` Descriptor of event =============== ==================================================================================== Writing ------- Writing tables in GWF format is not supported at this time.