gwpy.table.EventTable(data=None, masked=None, names=None, dtype=None, meta=None, copy=True, rows=None, copy_indices=True, **kwargs)[source]¶Bases: astropy.table.table.Table
A container for a table of events.
This object expands the default Table
with extra read/write formats, and methods to perform filtering,
rate calculations, and visualisation.
See also
astropy.table.Tablefor details on parameters for creating an EventTable
Attributes Summary
True if table has any mixin columns (defined as columns that are not Column subclasses). |
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Return a TableILoc object that can be used for retrieving indexed rows in the order they appear in the index. |
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Return the indices associated with columns of the table as a TableIndices object. |
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Return a TableLoc object that can be used for retrieving rows by index in a given data range. |
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Return a TableLocIndices object that can be used for retrieving the row indices corresponding to given table index key value or values. |
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Methods Summary
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Add a new Column object |
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Add a list of new Column objects |
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Insert a new index among one or more columns. |
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Add a new row to the end of the table. |
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Return the indices which would sort the table according to one or more key columns. |
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Return a new copy of the table in the form of a structured np.ndarray or np.ma.MaskedArray object (as appropriate). |
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Calculate an event rate |
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Cluster this |
Convert bytestring columns (dtype.kind=’S’) to unicode (dtype.kind=’U’) using UTF-8 encoding. |
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Convert unicode columns (dtype.kind=’U’) to bytestring (dtype.kind=’S’) using UTF-8 encoding. |
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Return a copy of the table. |
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Calculate the rate |
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Fetch a table of events from a database |
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Fetch events from an open-data catalogue hosted by GWOSC. |
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Return column[item] for recarray compatibility. |
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Return copy of self, with masked values filled. |
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Apply one or more column slice filters to this |
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Create a |
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Return the |
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Group this table by the specified |
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Generate a |
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Return the positional index of column |
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Return a context manager for an indexing mode. |
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Add a new row before the given |
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Iterate over the columns of this table. |
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Keep only the columns specified (remove the others). |
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Interactively browse table with a paging interface. |
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Return a list of lines for the formatted string representation of |
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Return a list of lines for the formatted string representation of |
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DEPRECATED, use |
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Print a formatted string representation of the table. |
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Print a formatted string representation of the entire table. |
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Read data into an |
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Remove a column from the table. |
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Remove several columns from the table. |
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Remove all indices involving the given column. |
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Remove a row from the table. |
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Remove rows from the table. |
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Rename a column. |
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Rename multiple columns. |
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Replace column |
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Reverse the row order of table rows. |
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Make a scatter plot of column |
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Render the table in HTML and show it in a web browser. |
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Render the table in HTML and show it in the IPython notebook. |
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Sort the table according to one or more keys. |
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Make a tile plot of this table. |
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Return a |
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Write this table to a file |
Attributes Documentation
ColumnClass¶colnames¶dtype¶groups¶has_mixin_columns¶True if table has any mixin columns (defined as columns that are not Column subclasses).
iloc¶Return a TableILoc object that can be used for retrieving indexed rows in the order they appear in the index.
indices¶Return the indices associated with columns of the table as a TableIndices object.
info(option='attributes', out='')¶loc¶Return a TableLoc object that can be used for retrieving rows by index in a given data range. Note that both loc and iloc work only with single-column indices.
loc_indices¶Return a TableLocIndices object that can be used for retrieving the row indices corresponding to given table index key value or values.
mask¶masked¶meta¶Methods Documentation
add_column(self, col, index=None, name=None, rename_duplicate=False, copy=True)¶Add a new Column object col to the table. If index
is supplied then insert column before index position
in the list of columns, otherwise append column to the end
of the list.
col : Column
Column object to add.
index : int or None
Insert column before this position or at end (default).
name : str
Column name
rename_duplicate : bool
Uniquify column name if it already exist. Default is False.
copy : bool
Make a copy of the new column. Default is True.
Examples
Create a table with two columns ‘a’ and ‘b’:
>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3]], names=('a', 'b'))
>>> print(t)
a b
--- ---
1 0.1
2 0.2
3 0.3
Create a third column ‘c’ and append it to the end of the table:
>>> col_c = Column(name='c', data=['x', 'y', 'z'])
>>> t.add_column(col_c)
>>> print(t)
a b c
--- --- ---
1 0.1 x
2 0.2 y
3 0.3 z
Add column ‘d’ at position 1. Note that the column is inserted before the given index:
>>> col_d = Column(name='d', data=['a', 'b', 'c'])
>>> t.add_column(col_d, 1)
>>> print(t)
a d b c
--- --- --- ---
1 a 0.1 x
2 b 0.2 y
3 c 0.3 z
Add second column named ‘b’ with rename_duplicate:
>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3]], names=('a', 'b'))
>>> col_b = Column(name='b', data=[1.1, 1.2, 1.3])
>>> t.add_column(col_b, rename_duplicate=True)
>>> print(t)
a b b_1
--- --- ---
1 0.1 1.1
2 0.2 1.2
3 0.3 1.3
Add an unnamed column or mixin object in the table using a default name
or by specifying an explicit name with name. Name can also be overridden:
>>> t = Table([[1, 2], [0.1, 0.2]], names=('a', 'b'))
>>> col_c = Column(data=['x', 'y'])
>>> t.add_column(col_c)
>>> t.add_column(col_c, name='c')
>>> col_b = Column(name='b', data=[1.1, 1.2])
>>> t.add_column(col_b, name='d')
>>> print(t)
a b col2 c d
--- --- ---- --- ---
1 0.1 x x 1.1
2 0.2 y y 1.2
To add several columns use add_columns.
add_columns(self, cols, indexes=None, names=None, copy=True, rename_duplicate=False)¶Add a list of new Column objects cols to the table. If a
corresponding list of indexes is supplied then insert column
before each index position in the original list of columns,
otherwise append columns to the end of the list.
cols : list of Columns
Column objects to add.
indexes : list of ints or None
Insert column before this position or at end (default).
names : list of str
Column names
copy : bool
Make a copy of the new columns. Default is True.
rename_duplicate : bool
Uniquify new column names if they duplicate the existing ones. Default is False.
Examples
Create a table with two columns ‘a’ and ‘b’:
>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3]], names=('a', 'b'))
>>> print(t)
a b
--- ---
1 0.1
2 0.2
3 0.3
Create column ‘c’ and ‘d’ and append them to the end of the table:
>>> col_c = Column(name='c', data=['x', 'y', 'z'])
>>> col_d = Column(name='d', data=['u', 'v', 'w'])
>>> t.add_columns([col_c, col_d])
>>> print(t)
a b c d
--- --- --- ---
1 0.1 x u
2 0.2 y v
3 0.3 z w
Add column ‘c’ at position 0 and column ‘d’ at position 1. Note that the columns are inserted before the given position:
>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3]], names=('a', 'b'))
>>> col_c = Column(name='c', data=['x', 'y', 'z'])
>>> col_d = Column(name='d', data=['u', 'v', 'w'])
>>> t.add_columns([col_c, col_d], [0, 1])
>>> print(t)
c a d b
--- --- --- ---
x 1 u 0.1
y 2 v 0.2
z 3 w 0.3
Add second column ‘b’ and column ‘c’ with rename_duplicate:
>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3]], names=('a', 'b'))
>>> col_b = Column(name='b', data=[1.1, 1.2, 1.3])
>>> col_c = Column(name='c', data=['x', 'y', 'z'])
>>> t.add_columns([col_b, col_c], rename_duplicate=True)
>>> print(t)
a b b_1 c
--- --- --- ---
1 0.1 1.1 x
2 0.2 1.2 y
3 0.3 1.3 z
Add unnamed columns or mixin objects in the table using default names
or by specifying explicit names with names. Names can also be overridden:
>>> t = Table()
>>> col_a = Column(data=['x', 'y'])
>>> col_b = Column(name='b', data=['u', 'v'])
>>> t.add_columns([col_a, col_b])
>>> t.add_columns([col_a, col_b], names=['c', 'd'])
>>> print(t)
col0 b c d
---- --- --- ---
x u x u
y v y v
add_index(self, colnames, engine=None, unique=False)¶Insert a new index among one or more columns. If there are no indices, make this index the primary table index.
colnames : str or list
List of column names (or a single column name) to index
engine : type or None
Indexing engine class to use, from among SortedArray, BST, FastBST, FastRBT, and SCEngine. If the supplied argument is None (by default), use SortedArray.
unique : bool
Whether the values of the index must be unique. Default is False.
add_row(self, vals=None, mask=None)¶Add a new row to the end of the table.
The vals argument can be:
Column values in the same order as table columns.
Keys corresponding to column names. Missing values will be filled with np.zeros for the column dtype.
NoneAll values filled with np.zeros for the column dtype.
This method requires that the Table object “owns” the underlying array data. In particular one cannot add a row to a Table that was initialized with copy=False from an existing array.
The mask attribute should give (if desired) the mask for the
values. The type of the mask should match that of the values, i.e. if
vals is an iterable, then mask should also be an iterable
with the same length, and if vals is a mapping, then mask
should be a dictionary.
vals : tuple, list, dict or None
Use the specified values in the new row
mask : tuple, list, dict or None
Use the specified mask values in the new row
Examples
Create a table with three columns ‘a’, ‘b’ and ‘c’:
>>> t = Table([[1,2],[4,5],[7,8]], names=('a','b','c'))
>>> print(t)
a b c
--- --- ---
1 4 7
2 5 8
Adding a new row with entries ‘3’ in ‘a’, ‘6’ in ‘b’ and ‘9’ in ‘c’:
>>> t.add_row([3,6,9])
>>> print(t)
a b c
--- --- ---
1 4 7
2 5 8
3 6 9
argsort(self, keys=None, kind=None, reverse=False)¶Return the indices which would sort the table according to one or
more key columns. This simply calls the numpy.argsort function on
the table with the order parameter set to keys.
keys : str or list of str
The column name(s) to order the table by
kind : {‘quicksort’, ‘mergesort’, ‘heapsort’}, optional
Sorting algorithm.
reverse : bool
Sort in reverse order (default=False)
index_array : ndarray, int
Array of indices that sorts the table by the specified key column(s).
as_array(self, keep_byteorder=False, names=None)¶Return a new copy of the table in the form of a structured np.ndarray or np.ma.MaskedArray object (as appropriate).
keep_byteorder : bool, optional
By default the returned array has all columns in native byte order. However, if this option is
Truethis preserves the byte order of all columns (if any are non-native).
names : list, optional:
List of column names to include for returned structured array. Default is to include all table columns.
table_array : np.ndarray (unmasked) or np.ma.MaskedArray (masked)
Copy of table as a numpy structured array
binned_event_rates(self, stride, column, bins, operator='>=', start=None, end=None, timecolumn=None)[source]¶Calculate an event rate TimeSeriesDict over
a number of bins.
stride : float
size (seconds) of each time bin
column : str
name of column by which to bin.
bins : list
one of:
'<','<=','>','>=','==','!=', for a standard mathematical operation,
'in'to use the list of bins as containing bin edges, ora callable function that takes compares an event value against the bin value and returns a boolean.
Note
If
binsis given as a list of tuples, this argument is ignored.
start : float, LIGOTimeGPS, optional
GPS start epoch of rate
TimeSeries.
end : float, LIGOTimeGPS, optional
GPS end time of rate
TimeSeries. This value will be rounded up to the nearest sample if needed.
timecolumn : str, optional, default: time
name of time-column to use when binning events
rates : ~gwpy.timeseries.TimeSeriesDict`
a dict of (bin,
TimeSeries) pairs describing a rate of events per second (Hz) for each of the bins.
cluster(self, index, rank, window)[source]¶Cluster this EventTable over a given column, index, maximizing
over a specified column in the table, rank.
The clustering algorithm uses a pooling method to identify groups
of points that are all separated in index by less than window.
Each cluster of nearby points is replaced by the point in that cluster
with the maximum value of rank.
index : str
name of the column which is used to search for clusters
rank : str
name of the column to maximize over in each cluster
window : float
window to use when clustering data points, will raise ValueError if
window > 0is not satisfied
table : EventTable
a new table that has had the clustering algorithm applied via slicing of the original
Examples
To cluster an EventTable (table) whose index is
end_time, window is 0.1, and maximize over snr:
>>> table.cluster('end_time', 'snr', 0.1)
convert_bytestring_to_unicode(self)¶Convert bytestring columns (dtype.kind=’S’) to unicode (dtype.kind=’U’) using UTF-8 encoding.
Internally this changes string columns to represent each character in the string with a 4-byte UCS-4 equivalent, so it is inefficient for memory but allows scripts to manipulate string arrays with natural syntax.
convert_unicode_to_bytestring(self)¶Convert unicode columns (dtype.kind=’U’) to bytestring (dtype.kind=’S’) using UTF-8 encoding.
When exporting a unicode string array to a file, it may be desirable to encode unicode columns as bytestrings.
copy(self, copy_data=True)¶Return a copy of the table.
copy_data : bool
If
True(the default), copy the underlying data array. Otherwise, use the same data array. Themetais always deepcopied regardless of the value forcopy_data.
event_rate(self, stride, start=None, end=None, timecolumn=None)[source]¶Calculate the rate TimeSeries for this Table.
stride : float
size (seconds) of each time bin
start : float, LIGOTimeGPS, optional
GPS start epoch of rate
TimeSeries
end : float, LIGOTimeGPS, optional
GPS end time of rate
TimeSeries. This value will be rounded up to the nearest sample if needed.
timecolumn : str, optional
name of time-column to use when binning events, attempts are made to guess this
rate : TimeSeries
a
TimeSeriesof events per second (Hz)
ValueError
if the
timecolumncannot be guessed from the table contents
fetch(format_, *args, **kwargs)[source]¶Fetch a table of events from a database
format : str, Engine
the format of the remote data, see _Notes_ for a list of registered formats, OR an SQL database
Engineobject
*args
all other positional arguments are specific to the data format, see below for basic usage
columns : list of str, optional
the columns to fetch from the database table, defaults to all
selection : str, or list of str, optional
one or more column filters with which to downselect the returned table rows as they as read, e.g.
'snr > 5'; multiple selections should be connected by ‘ && ‘, or given as alist, e.g.'snr > 5 && frequency < 1000'or['snr > 5', 'frequency < 1000']
**kwargs
all other positional arguments are specific to the data format, see the online documentation for more details
table : EventTable
a table of events recovered from the remote database
Notes
The available named formats are:
Format |
Basic usage |
|---|---|
gravityspy |
|
hacr |
|
Examples
>>> from gwpy.table import EventTable
To download a table of all blip glitches from the Gravity Spy database:
>>> EventTable.fetch('gravityspy', 'glitches', selection='Label=Blip')
To download a table from any SQL-type server
>>> from sqlalchemy.engine import create_engine
>>> engine = create_engine(...)
>>> EventTable.fetch(engine, 'mytable')
fetch_open_data(catalog, columns=None, selection=None, host='https://www.gw-openscience.org', **kwargs)[source]¶Fetch events from an open-data catalogue hosted by GWOSC.
catalog : str
the name of the catalog to fetch, e.g.
'GWTC-1-confident'
columns : list of str, optional
the list of column names to read
selection : str, or list of str, optional
one or more column filters with which to downselect the returned events as they as read, e.g.
'mass1 < 30'; multiple selections should be connected by ‘ && ‘, or given as alist, e.g.'mchirp < 3 && distance < 500'or['mchirp < 3', 'distance < 500']
host : str, optional
the open-data host to use
field(self, item)¶Return column[item] for recarray compatibility.
filled(self, fill_value=None)¶Return copy of self, with masked values filled.
If input fill_value supplied then that value is used for all
masked entries in the table. Otherwise the individual
fill_value defined for each table column is used.
fill_value : str
If supplied, this
fill_valueis used for all masked entries in the entire table.
filled_table : Table
New table with masked values filled
filter(self, *column_filters)[source]¶Apply one or more column slice filters to this EventTable
Multiple column filters can be given, and will be applied concurrently
a column slice filter definition, e.g.
'snr > 10, or a filter tuple definition, e.g.('snr', <my_func>, <arg>)
table : EventTable
a new table with only those rows matching the filters
Notes
See Filtering tables for more details on using filter tuples
Examples
To filter an existing EventTable (table) to include only
rows with snr greater than 10, and frequency less than
1000:
>>> table.filter('snr>10', 'frequency<1000')
Custom operations can be defined using filter tuple definitions:
>>> from gwpy.table.filters import in_segmentlist
>>> filter(my_table, ('time', in_segmentlist, segs))
from_pandas(dataframe, index=False)¶Create a Table from a pandas.DataFrame instance
In addition to converting generic numeric or string columns, this supports
conversion of pandas Date and Time delta columns to Time
and TimeDelta columns, respectively.
dataframe : pandas.DataFrame
A pandas
pandas.DataFrameinstance
index : bool
Include the index column in the returned table (default=False)
table : Table
A
Table(or subclass) instance
ImportError
If pandas is not installed
Examples
Here we convert a pandas.DataFrame instance
to a QTable.
>>> import numpy as np
>>> import pandas as pd
>>> from astropy.table import QTable
>>> time = pd.Series(['1998-01-01', '2002-01-01'], dtype='datetime64[ns]')
>>> dt = pd.Series(np.array([1, 300], dtype='timedelta64[s]'))
>>> df = pd.DataFrame({'time': time})
>>> df['dt'] = dt
>>> df['x'] = [3., 4.]
>>> with pd.option_context('display.max_columns', 20):
... print(df)
time dt x
0 1998-01-01 00:00:01 3.0
1 2002-01-01 00:05:00 4.0
>>> QTable.from_pandas(df)
<QTable length=2>
time dt x
object object float64
----------------------- ------ -------
1998-01-01T00:00:00.000 1.0 3.0
2002-01-01T00:00:00.000 300.0 4.0
get_column(self, name)[source]¶Return the Column with the given name
This method is provided only for compatibility with the
ligo.lw.table.Table.
name : str
the name of the column to return
astropy.table.ColumnKeyError
if no column is found with the given name
group_by(self, keys)¶Group this table by the specified keys
This effectively splits the table into groups which correspond to unique
values of the keys grouping object. The output is a new
TableGroups which contains a copy of this table but
sorted by row according to keys.
The keys input to group_by can be specified in different ways:
String or list of strings corresponding to table column name(s)
Numpy array (homogeneous or structured) with same length as this table
Tablewith same length as this table
hist(self, column, **kwargs)[source]¶Generate a HistogramPlot of this Table.
column : str
Name of the column over which to histogram data
method : str, optional
Name of
Axesmethod to use to plot the histogram, default:'hist'.
**kwargs
Any other keyword arguments, see below.
plot : Plot
The newly created figure.
See also
matplotlib.pyplot.figurefor documentation of keyword arguments used to create the figure.
matplotlib.figure.Figure.add_subplotfor documentation of keyword arguments used to create the axes.
gwpy.plot.Axes.histfor documentation of keyword arguments used to display the histogram, if the method keyword is given, this method might not actually be the one used.
index_column(self, name)¶Return the positional index of column name.
name : str
column name
index : int
Positional index of column
name.
Examples
Create a table with three columns ‘a’, ‘b’ and ‘c’:
>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3], ['x', 'y', 'z']],
... names=('a', 'b', 'c'))
>>> print(t)
a b c
--- --- ---
1 0.1 x
2 0.2 y
3 0.3 z
Get index of column ‘b’ of the table:
>>> t.index_column('b')
1
index_mode(self, mode)¶Return a context manager for an indexing mode.
mode : str
Either ‘freeze’, ‘copy_on_getitem’, or ‘discard_on_copy’. In ‘discard_on_copy’ mode, indices are not copied whenever columns or tables are copied. In ‘freeze’ mode, indices are not modified whenever columns are modified; at the exit of the context, indices refresh themselves based on column values. This mode is intended for scenarios in which one intends to make many additions or modifications in an indexed column. In ‘copy_on_getitem’ mode, indices are copied when taking column slices as well as table slices, so col[i0:i1] will preserve indices.
insert_row(self, index, vals=None, mask=None)¶Add a new row before the given index position in the table.
The vals argument can be:
Column values in the same order as table columns.
Keys corresponding to column names. Missing values will be filled with np.zeros for the column dtype.
NoneAll values filled with np.zeros for the column dtype.
The mask attribute should give (if desired) the mask for the
values. The type of the mask should match that of the values, i.e. if
vals is an iterable, then mask should also be an iterable
with the same length, and if vals is a mapping, then mask
should be a dictionary.
itercols(self)¶Iterate over the columns of this table.
Examples
To iterate over the columns of a table:
>>> t = Table([[1], [2]])
>>> for col in t.itercols():
... print(col)
col0
----
1
col1
----
2
Using itercols() is similar to for col in t.columns.values()
but is syntactically preferred.
keep_columns(self, names)¶Keep only the columns specified (remove the others).
names : list
A list containing the names of the columns to keep. All other columns will be removed.
Examples
Create a table with three columns ‘a’, ‘b’ and ‘c’:
>>> t = Table([[1, 2, 3],[0.1, 0.2, 0.3],['x', 'y', 'z']],
... names=('a', 'b', 'c'))
>>> print(t)
a b c
--- --- ---
1 0.1 x
2 0.2 y
3 0.3 z
Specifying only a single column name keeps only this column. Keep only column ‘a’ of the table:
>>> t.keep_columns('a')
>>> print(t)
a
---
1
2
3
Specifying a list of column names is keeps is also possible. Keep columns ‘a’ and ‘c’ of the table:
>>> t = Table([[1, 2, 3],[0.1, 0.2, 0.3],['x', 'y', 'z']],
... names=('a', 'b', 'c'))
>>> t.keep_columns(['a', 'c'])
>>> print(t)
a c
--- ---
1 x
2 y
3 z
keys(self)¶more(self, max_lines=None, max_width=None, show_name=True, show_unit=None, show_dtype=False)¶Interactively browse table with a paging interface.
Supported keys:
f, <space> : forward one page
b : back one page
r : refresh same page
n : next row
p : previous row
< : go to beginning
> : go to end
q : quit browsing
h : print this help
max_lines : int
Maximum number of lines in table output
max_width : int or None
Maximum character width of output
show_name : bool
Include a header row for column names. Default is True.
show_unit : bool
Include a header row for unit. Default is to show a row for units only if one or more columns has a defined value for the unit.
show_dtype : bool
Include a header row for column dtypes. Default is True.
pformat(self, max_lines=None, max_width=None, show_name=True, show_unit=None, show_dtype=False, html=False, tableid=None, align=None, tableclass=None)¶the table.
If no value of max_lines is supplied then the height of the
screen terminal is used to set max_lines. If the terminal
height cannot be determined then the default is taken from the
configuration item astropy.conf.max_lines. If a negative
value of max_lines is supplied then there is no line limit
applied.
The same applies for max_width except the configuration item is
astropy.conf.max_width.
max_lines : int or None
Maximum number of rows to output
max_width : int or None
Maximum character width of output
show_name : bool
Include a header row for column names. Default is True.
show_unit : bool
Include a header row for unit. Default is to show a row for units only if one or more columns has a defined value for the unit.
show_dtype : bool
Include a header row for column dtypes. Default is True.
html : bool
Format the output as an HTML table. Default is False.
tableid : str or None
An ID tag for the table; only used if html is set. Default is “table{id}”, where id is the unique integer id of the table object, id(self)
align : str or list or tuple or None
Left/right alignment of columns. Default is right (None) for all columns. Other allowed values are ‘>’, ‘<’, ‘^’, and ‘0=’ for right, left, centered, and 0-padded, respectively. A list of strings can be provided for alignment of tables with multiple columns.
tableclass : str or list of str or None
CSS classes for the table; only used if html is set. Default is None.
lines : list
Formatted table as a list of strings.
pformat_all(self, max_lines=-1, max_width=-1, show_name=True, show_unit=None, show_dtype=False, html=False, tableid=None, align=None, tableclass=None)¶the entire table.
If no value of max_lines is supplied then the height of the
screen terminal is used to set max_lines. If the terminal
height cannot be determined then the default is taken from the
configuration item astropy.conf.max_lines. If a negative
value of max_lines is supplied then there is no line limit
applied.
The same applies for max_width except the configuration item is
astropy.conf.max_width.
max_lines : int or None
Maximum number of rows to output
max_width : int or None
Maximum character width of output
show_name : bool
Include a header row for column names. Default is True.
show_unit : bool
Include a header row for unit. Default is to show a row for units only if one or more columns has a defined value for the unit.
show_dtype : bool
Include a header row for column dtypes. Default is True.
html : bool
Format the output as an HTML table. Default is False.
tableid : str or None
An ID tag for the table; only used if html is set. Default is “table{id}”, where id is the unique integer id of the table object, id(self)
align : str or list or tuple or None
Left/right alignment of columns. Default is right (None) for all columns. Other allowed values are ‘>’, ‘<’, ‘^’, and ‘0=’ for right, left, centered, and 0-padded, respectively. A list of strings can be provided for alignment of tables with multiple columns.
tableclass : str or list of str or None
CSS classes for the table; only used if html is set. Default is None.
lines : list
Formatted table as a list of strings.
plot(self, *args, **kwargs)[source]¶DEPRECATED, use EventTable.scatter
pprint(self, max_lines=None, max_width=None, show_name=True, show_unit=None, show_dtype=False, align=None)¶Print a formatted string representation of the table.
If no value of
max_linesis supplied then the height of the screen terminal is used to setmax_lines. If the terminal height cannot be determined then the default is taken from the configuration itemastropy.conf.max_lines. If a negative value ofmax_linesis supplied then there is no line limit applied.The same applies for max_width except the configuration item is
astropy.conf.max_width.
max_lines : int or None
Maximum number of lines in table output.
max_width : int or None
Maximum character width of output.
show_name : bool
Include a header row for column names. Default is True.
show_unit : bool
Include a header row for unit. Default is to show a row for units only if one or more columns has a defined value for the unit.
show_dtype : bool
Include a header row for column dtypes. Default is True.
align : str or list or tuple or None
Left/right alignment of columns. Default is right (None) for all columns. Other allowed values are ‘>’, ‘<’, ‘^’, and ‘0=’ for right, left, centered, and 0-padded, respectively. A list of strings can be provided for alignment of tables with multiple columns.
pprint_all(self, max_lines=-1, max_width=-1, show_name=True, show_unit=None, show_dtype=False, align=None)¶Print a formatted string representation of the entire table.
This method is the same as
astropy.table.Table.pprintexcept that the defaultmax_linesandmax_widthare both -1 so that by default the entire table is printed instead of restricting to the size of the screen terminal.
max_lines : int or None
Maximum number of lines in table output.
max_width : int or None
Maximum character width of output.
show_name : bool
Include a header row for column names. Default is True.
show_unit : bool
Include a header row for unit. Default is to show a row for units only if one or more columns has a defined value for the unit.
show_dtype : bool
Include a header row for column dtypes. Default is True.
align : str or list or tuple or None
Left/right alignment of columns. Default is right (None) for all columns. Other allowed values are ‘>’, ‘<’, ‘^’, and ‘0=’ for right, left, centered, and 0-padded, respectively. A list of strings can be provided for alignment of tables with multiple columns.
read(source, *args, **kwargs)[source]¶Read data into an EventTable
*args
other positional arguments will be passed directly to the underlying reader method for the given format
format : str, optional
the format of the given source files; if not given, an attempt will be made to automatically identify the format
columns : list of str, optional
the list of column names to read
selection : str, or list of str, optional
one or more column filters with which to downselect the returned table rows as they as read, e.g.
'snr > 5'; multiple selections should be connected by ‘ && ‘, or given as alist, e.g.'snr > 5 && frequency < 1000'or['snr > 5', 'frequency < 1000']
nproc : int, optional, default: 1
number of CPUs to use for parallel reading of multiple files
verbose : bool, optional
print a progress bar showing read status, default:
False
.. note::
Keyword arguments other than those listed here may be required depending on the
format
EventTableastropy.io.registry.IORegistryError
if the
formatcannot be automatically identified
IndexError
if
sourceis an empty list
Notes
The available built-in formats are:
Format |
Read |
Write |
Auto-identify |
Deprecated |
|---|---|---|---|---|
ascii |
Yes |
Yes |
No |
|
ascii.aastex |
Yes |
Yes |
No |
|
ascii.basic |
Yes |
Yes |
No |
|
ascii.cds |
Yes |
No |
No |
|
ascii.commented_header |
Yes |
Yes |
No |
|
ascii.csv |
Yes |
Yes |
Yes |
|
ascii.cwb |
Yes |
No |
No |
|
ascii.daophot |
Yes |
No |
No |
|
ascii.ecsv |
Yes |
Yes |
Yes |
|
ascii.fast_basic |
Yes |
Yes |
No |
|
ascii.fast_commented_header |
Yes |
Yes |
No |
|
ascii.fast_csv |
Yes |
Yes |
No |
|
ascii.fast_no_header |
Yes |
Yes |
No |
|
ascii.fast_rdb |
Yes |
Yes |
No |
|
ascii.fast_tab |
Yes |
Yes |
No |
|
ascii.fixed_width |
Yes |
Yes |
No |
|
ascii.fixed_width_no_header |
Yes |
Yes |
No |
|
ascii.fixed_width_two_line |
Yes |
Yes |
No |
|
ascii.html |
Yes |
Yes |
Yes |
|
ascii.ipac |
Yes |
Yes |
No |
|
ascii.latex |
Yes |
Yes |
Yes |
|
ascii.no_header |
Yes |
Yes |
No |
|
ascii.omega |
Yes |
No |
No |
|
ascii.rdb |
Yes |
Yes |
Yes |
|
ascii.rst |
Yes |
Yes |
No |
|
ascii.sextractor |
Yes |
No |
No |
|
ascii.tab |
Yes |
Yes |
No |
|
asdf |
Yes |
Yes |
Yes |
|
fits |
Yes |
Yes |
Yes |
|
gwf |
Yes |
Yes |
Yes |
|
hdf5 |
Yes |
Yes |
Yes |
|
hdf5.pycbc_live |
Yes |
No |
Yes |
|
hdf5.snax |
Yes |
No |
No |
|
ligolw |
Yes |
Yes |
Yes |
|
pandas.csv |
Yes |
Yes |
No |
|
pandas.fwf |
Yes |
No |
No |
|
pandas.html |
Yes |
Yes |
No |
|
pandas.json |
Yes |
Yes |
No |
|
root |
Yes |
Yes |
Yes |
|
root.cwb |
Yes |
No |
No |
|
root.omicron |
Yes |
No |
No |
|
votable |
Yes |
Yes |
Yes |
|
aastex |
Yes |
Yes |
No |
Yes |
cds |
Yes |
No |
No |
Yes |
csv |
Yes |
Yes |
No |
Yes |
daophot |
Yes |
No |
No |
Yes |
html |
Yes |
Yes |
No |
Yes |
ipac |
Yes |
Yes |
No |
Yes |
latex |
Yes |
Yes |
No |
Yes |
rdb |
Yes |
Yes |
No |
Yes |
Deprecated format names like aastex will be removed in a future version. Use the full
name (e.g. ascii.aastex) instead.
remove_column(self, name)¶Remove a column from the table.
This can also be done with:
del table[name]
name : str
Name of column to remove
Examples
Create a table with three columns ‘a’, ‘b’ and ‘c’:
>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3], ['x', 'y', 'z']],
... names=('a', 'b', 'c'))
>>> print(t)
a b c
--- --- ---
1 0.1 x
2 0.2 y
3 0.3 z
Remove column ‘b’ from the table:
>>> t.remove_column('b')
>>> print(t)
a c
--- ---
1 x
2 y
3 z
To remove several columns at the same time use remove_columns.
remove_columns(self, names)¶Remove several columns from the table.
names : list
A list containing the names of the columns to remove
Examples
Create a table with three columns ‘a’, ‘b’ and ‘c’:
>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3], ['x', 'y', 'z']],
... names=('a', 'b', 'c'))
>>> print(t)
a b c
--- --- ---
1 0.1 x
2 0.2 y
3 0.3 z
Remove columns ‘b’ and ‘c’ from the table:
>>> t.remove_columns(['b', 'c'])
>>> print(t)
a
---
1
2
3
Specifying only a single column also works. Remove column ‘b’ from the table:
>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3], ['x', 'y', 'z']],
... names=('a', 'b', 'c'))
>>> t.remove_columns('b')
>>> print(t)
a c
--- ---
1 x
2 y
3 z
This gives the same as using remove_column.
remove_indices(self, colname)¶Remove all indices involving the given column. If the primary index is removed, the new primary index will be the most recently added remaining index.
colname : str
Name of column
remove_row(self, index)¶Remove a row from the table.
index : int
Index of row to remove
Examples
Create a table with three columns ‘a’, ‘b’ and ‘c’:
>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3], ['x', 'y', 'z']],
... names=('a', 'b', 'c'))
>>> print(t)
a b c
--- --- ---
1 0.1 x
2 0.2 y
3 0.3 z
Remove row 1 from the table:
>>> t.remove_row(1)
>>> print(t)
a b c
--- --- ---
1 0.1 x
3 0.3 z
To remove several rows at the same time use remove_rows.
remove_rows(self, row_specifier)¶Remove rows from the table.
row_specifier : slice, int, or array of ints
Specification for rows to remove
Examples
Create a table with three columns ‘a’, ‘b’ and ‘c’:
>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3], ['x', 'y', 'z']],
... names=('a', 'b', 'c'))
>>> print(t)
a b c
--- --- ---
1 0.1 x
2 0.2 y
3 0.3 z
Remove rows 0 and 2 from the table:
>>> t.remove_rows([0, 2])
>>> print(t)
a b c
--- --- ---
2 0.2 y
Note that there are no warnings if the slice operator extends outside the data:
>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3], ['x', 'y', 'z']],
... names=('a', 'b', 'c'))
>>> t.remove_rows(slice(10, 20, 1))
>>> print(t)
a b c
--- --- ---
1 0.1 x
2 0.2 y
3 0.3 z
rename_column(self, name, new_name)¶Rename a column.
This can also be done directly with by setting the name attribute
for a column:
table[name].name = new_name
TODO: this won’t work for mixins
name : str
The current name of the column.
new_name : str
The new name for the column
Examples
Create a table with three columns ‘a’, ‘b’ and ‘c’:
>>> t = Table([[1,2],[3,4],[5,6]], names=('a','b','c'))
>>> print(t)
a b c
--- --- ---
1 3 5
2 4 6
Renaming column ‘a’ to ‘aa’:
>>> t.rename_column('a' , 'aa')
>>> print(t)
aa b c
--- --- ---
1 3 5
2 4 6
rename_columns(self, names, new_names)¶Rename multiple columns.
names : list, tuple
A list or tuple of existing column names.
new_names : list, tuple
A list or tuple of new column names.
Examples
Create a table with three columns ‘a’, ‘b’, ‘c’:
>>> t = Table([[1,2],[3,4],[5,6]], names=('a','b','c'))
>>> print(t)
a b c
--- --- ---
1 3 5
2 4 6
Renaming columns ‘a’ to ‘aa’ and ‘b’ to ‘bb’:
>>> names = ('a','b')
>>> new_names = ('aa','bb')
>>> t.rename_columns(names, new_names)
>>> print(t)
aa bb c
--- --- ---
1 3 5
2 4 6
replace_column(self, name, col)¶Replace column name with the new col object.
name : str
Name of column to replace
col : column object (list, ndarray, Column, etc)
New column object to replace the existing column
Examples
Replace column ‘a’ with a float version of itself:
>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3]], names=('a', 'b'))
>>> float_a = t['a'].astype(float)
>>> t.replace_column('a', float_a)
reverse(self)¶Reverse the row order of table rows. The table is reversed in place and there are no function arguments.
Examples
Create a table with three columns:
>>> t = Table([['Max', 'Jo', 'John'], ['Miller','Miller','Jackson'],
... [12,15,18]], names=('firstname','name','tel'))
>>> print(t)
firstname name tel
--------- ------- ---
Max Miller 12
Jo Miller 15
John Jackson 18
Reversing order:
>>> t.reverse()
>>> print(t)
firstname name tel
--------- ------- ---
John Jackson 18
Jo Miller 15
Max Miller 12
scatter(self, x, y, **kwargs)[source]¶Make a scatter plot of column x vs column y.
x : str
name of column defining centre point on the X-axis
y : str
name of column defining centre point on the Y-axis
color : str, optional, default:None
name of column by which to color markers
**kwargs
any other keyword arguments, see below
plot : Plot
the newly created figure
See also
matplotlib.pyplot.figurefor documentation of keyword arguments used to create the figure
matplotlib.figure.Figure.add_subplotfor documentation of keyword arguments used to create the axes
gwpy.plot.Axes.scatterfor documentation of keyword arguments used to display the table
show_in_browser(self, max_lines=5000, jsviewer=False, browser='default', jskwargs={'use_local_files': True}, tableid=None, table_class='display compact', css=None, show_row_index='idx')¶Render the table in HTML and show it in a web browser.
max_lines : int
Maximum number of rows to export to the table (set low by default to avoid memory issues, since the browser view requires duplicating the table in memory). A negative value of
max_linesindicates no row limit.
jsviewer : bool
If
True, prepends some javascript headers so that the table is rendered as a DataTables data table. This allows in-browser searching & sorting.
browser : str
Any legal browser name, e.g.
'firefox','chrome','safari'(for mac, you may need to use'open -a "/Applications/Google Chrome.app" {}'for Chrome). If'default', will use the system default browser.
jskwargs : dict
Passed to the
astropy.table.JSViewerinit. Defaults to{'use_local_files': True}which means that the JavaScript libraries will be served from local copies.
tableid : str or None
An html ID tag for the table. Default is
table{id}, where id is the unique integer id of the table object, id(self).
table_class : str or None
A string with a list of HTML classes used to style the table. Default is “display compact”, and other possible values can be found in https://www.datatables.net/manual/styling/classes
css : string
A valid CSS string declaring the formatting for the table. Defaults to
astropy.table.jsviewer.DEFAULT_CSS.
show_row_index : str or False
If this does not evaluate to False, a column with the given name will be added to the version of the table that gets displayed. This new column shows the index of the row in the table itself, even when the displayed table is re-sorted by another column. Note that if a column with this name already exists, this option will be ignored. Defaults to “idx”.
show_in_notebook(self, tableid=None, css=None, display_length=50, table_class='astropy-default', show_row_index='idx')¶Render the table in HTML and show it in the IPython notebook.
tableid : str or None
An html ID tag for the table. Default is
table{id}-XXX, where id is the unique integer id of the table object, id(self), and XXX is a random number to avoid conflicts when printing the same table multiple times.
table_class : str or None
A string with a list of HTML classes used to style the table. The special default string (‘astropy-default’) means that the string will be retrieved from the configuration item
astropy.table.default_notebook_table_class. Note that these table classes may make use of bootstrap, as this is loaded with the notebook. See this page for the list of classes.
css : string
A valid CSS string declaring the formatting for the table. Defaults to
astropy.table.jsviewer.DEFAULT_CSS_NB.
display_length : int, optional
Number or rows to show. Defaults to 50.
show_row_index : str or False
If this does not evaluate to False, a column with the given name will be added to the version of the table that gets displayed. This new column shows the index of the row in the table itself, even when the displayed table is re-sorted by another column. Note that if a column with this name already exists, this option will be ignored. Defaults to “idx”.
Notes
Currently, unlike show_in_browser (with jsviewer=True), this
method needs to access online javascript code repositories. This is due
to modern browsers’ limitations on accessing local files. Hence, if you
call this method while offline (and don’t have a cached version of
jquery and jquery.dataTables), you will not get the jsviewer features.
sort(self, keys=None, reverse=False)¶Sort the table according to one or more keys. This operates on the existing table and does not return a new table.
keys : str or list of str
The key(s) to order the table by. If None, use the primary index of the Table.
reverse : bool
Sort in reverse order (default=False)
Examples
Create a table with 3 columns:
>>> t = Table([['Max', 'Jo', 'John'], ['Miller', 'Miller', 'Jackson'],
... [12, 15, 18]], names=('firstname', 'name', 'tel'))
>>> print(t)
firstname name tel
--------- ------- ---
Max Miller 12
Jo Miller 15
John Jackson 18
Sorting according to standard sorting rules, first ‘name’ then ‘firstname’:
>>> t.sort(['name', 'firstname'])
>>> print(t)
firstname name tel
--------- ------- ---
John Jackson 18
Jo Miller 15
Max Miller 12
Sorting according to standard sorting rules, first ‘firstname’ then ‘tel’, in reverse order:
>>> t.sort(['firstname', 'tel'], reverse=True)
>>> print(t)
firstname name tel
--------- ------- ---
Max Miller 12
John Jackson 18
Jo Miller 15
tile(self, x, y, w, h, **kwargs)[source]¶Make a tile plot of this table.
x : str
name of column defining anchor point on the X-axis
y : str
name of column defining anchor point on the Y-axis
w : str
name of column defining extent on the X-axis (width)
h : str
name of column defining extent on the Y-axis (height)
color : str, optional, default:None
name of column by which to color markers
**kwargs
any other keyword arguments, see below
plot : Plot
the newly created figure
See also
matplotlib.pyplot.figurefor documentation of keyword arguments used to create the figure
matplotlib.figure.Figure.add_subplotfor documentation of keyword arguments used to create the axes
gwpy.plot.Axes.tilefor documentation of keyword arguments used to display the table
to_pandas(self, index=None)¶Return a pandas.DataFrame instance
The index of the created DataFrame is controlled by the index
argument. For index=True or the default None, an index will be
specified for the DataFrame if there is a primary key index on the
Table and if it corresponds to a single column. If index=False
then no DataFrame index will be specified. If index is the name of
a column in the table then that will be the DataFrame index.
In additional to vanilla columns or masked columns, this supports Table
mixin columns like Quantity, Time, or SkyCoord. In many cases these
objects have no analog in pandas and will be converted to a “encoded”
representation using only Column or MaskedColumn. The exception is
Time or TimeDelta columns, which will be converted to the corresponding
representation in pandas using np.datetime64 or np.timedelta64.
See the example below.
dataframe : pandas.DataFrame
A pandas
pandas.DataFrameinstance
index : None, bool, str
Specify DataFrame index mode
ImportError
If pandas is not installed
ValueError
If the Table has multi-dimensional columns
Examples
Here we convert a table with a few mixins to a
pandas.DataFrame instance.
>>> import pandas as pd
>>> from astropy.table import QTable
>>> import astropy.units as u
>>> from astropy.time import Time, TimeDelta
>>> from astropy.coordinates import SkyCoord
>>> q = [1, 2] * u.m
>>> tm = Time([1998, 2002], format='jyear')
>>> sc = SkyCoord([5, 6], [7, 8], unit='deg')
>>> dt = TimeDelta([3, 200] * u.s)
>>> t = QTable([q, tm, sc, dt], names=['q', 'tm', 'sc', 'dt'])
>>> df = t.to_pandas(index='tm')
>>> with pd.option_context('display.max_columns', 20):
... print(df)
q sc.ra sc.dec dt
tm
1998-01-01 1.0 5.0 7.0 00:00:03
2002-01-01 2.0 6.0 8.0 00:03:20
write(self, target, *args, **kwargs)[source]¶Write this table to a file
target: `str`
filename for output data file
*args
other positional arguments will be passed directly to the underlying writer method for the given format
format : str, optional
format for output data; if not given, an attempt will be made to automatically identify the format based on the
targetfilename
**kwargs
other keyword arguments will be passed directly to the underlying writer method for the given format
astropy.io.registry.IORegistryError
if the
formatcannot be automatically identified
Notes
The available built-in formats are:
Format |
Read |
Write |
Auto-identify |
Deprecated |
|---|---|---|---|---|
ascii |
Yes |
Yes |
No |
|
ascii.aastex |
Yes |
Yes |
No |
|
ascii.basic |
Yes |
Yes |
No |
|
ascii.commented_header |
Yes |
Yes |
No |
|
ascii.csv |
Yes |
Yes |
Yes |
|
ascii.ecsv |
Yes |
Yes |
Yes |
|
ascii.fast_basic |
Yes |
Yes |
No |
|
ascii.fast_commented_header |
Yes |
Yes |
No |
|
ascii.fast_csv |
Yes |
Yes |
No |
|
ascii.fast_no_header |
Yes |
Yes |
No |
|
ascii.fast_rdb |
Yes |
Yes |
No |
|
ascii.fast_tab |
Yes |
Yes |
No |
|
ascii.fixed_width |
Yes |
Yes |
No |
|
ascii.fixed_width_no_header |
Yes |
Yes |
No |
|
ascii.fixed_width_two_line |
Yes |
Yes |
No |
|
ascii.html |
Yes |
Yes |
Yes |
|
ascii.ipac |
Yes |
Yes |
No |
|
ascii.latex |
Yes |
Yes |
Yes |
|
ascii.no_header |
Yes |
Yes |
No |
|
ascii.rdb |
Yes |
Yes |
Yes |
|
ascii.rst |
Yes |
Yes |
No |
|
ascii.tab |
Yes |
Yes |
No |
|
asdf |
Yes |
Yes |
Yes |
|
fits |
Yes |
Yes |
Yes |
|
gwf |
Yes |
Yes |
No |
|
hdf5 |
Yes |
Yes |
Yes |
|
jsviewer |
No |
Yes |
No |
|
ligolw |
Yes |
Yes |
Yes |
|
pandas.csv |
Yes |
Yes |
No |
|
pandas.html |
Yes |
Yes |
No |
|
pandas.json |
Yes |
Yes |
No |
|
root |
Yes |
Yes |
Yes |
|
votable |
Yes |
Yes |
Yes |
|
aastex |
Yes |
Yes |
No |
Yes |
csv |
Yes |
Yes |
No |
Yes |
html |
Yes |
Yes |
No |
Yes |
ipac |
Yes |
Yes |
No |
Yes |
latex |
Yes |
Yes |
No |
Yes |
rdb |
Yes |
Yes |
No |
Yes |
Deprecated format names like aastex will be removed in a future version. Use the full
name (e.g. ascii.aastex) instead.
binned_event_rates(self, stride, column, bins, operator='>=', start=None, end=None, timecolumn=None)[source]Calculate an event rate TimeSeriesDict over
a number of bins.
stride : float
size (seconds) of each time bin
column : str
name of column by which to bin.
bins : list
one of:
'<','<=','>','>=','==','!=', for a standard mathematical operation,
'in'to use the list of bins as containing bin edges, ora callable function that takes compares an event value against the bin value and returns a boolean.
Note
If
binsis given as a list of tuples, this argument is ignored.
start : float, LIGOTimeGPS, optional
GPS start epoch of rate
TimeSeries.
end : float, LIGOTimeGPS, optional
GPS end time of rate
TimeSeries. This value will be rounded up to the nearest sample if needed.
timecolumn : str, optional, default: time
name of time-column to use when binning events
rates : ~gwpy.timeseries.TimeSeriesDict`
a dict of (bin,
TimeSeries) pairs describing a rate of events per second (Hz) for each of the bins.
cluster(self, index, rank, window)[source]Cluster this EventTable over a given column, index, maximizing
over a specified column in the table, rank.
The clustering algorithm uses a pooling method to identify groups
of points that are all separated in index by less than window.
Each cluster of nearby points is replaced by the point in that cluster
with the maximum value of rank.
index : str
name of the column which is used to search for clusters
rank : str
name of the column to maximize over in each cluster
window : float
window to use when clustering data points, will raise ValueError if
window > 0is not satisfied
table : EventTable
a new table that has had the clustering algorithm applied via slicing of the original
Examples
To cluster an EventTable (table) whose index is
end_time, window is 0.1, and maximize over snr:
>>> table.cluster('end_time', 'snr', 0.1)
event_rate(self, stride, start=None, end=None, timecolumn=None)[source]Calculate the rate TimeSeries for this Table.
stride : float
size (seconds) of each time bin
start : float, LIGOTimeGPS, optional
GPS start epoch of rate
TimeSeries
end : float, LIGOTimeGPS, optional
GPS end time of rate
TimeSeries. This value will be rounded up to the nearest sample if needed.
timecolumn : str, optional
name of time-column to use when binning events, attempts are made to guess this
rate : TimeSeries
a
TimeSeriesof events per second (Hz)
ValueError
if the
timecolumncannot be guessed from the table contents
fetch(format_, *args, **kwargs)[source]Fetch a table of events from a database
format : str, Engine
the format of the remote data, see _Notes_ for a list of registered formats, OR an SQL database
Engineobject
*args
all other positional arguments are specific to the data format, see below for basic usage
columns : list of str, optional
the columns to fetch from the database table, defaults to all
selection : str, or list of str, optional
one or more column filters with which to downselect the returned table rows as they as read, e.g.
'snr > 5'; multiple selections should be connected by ‘ && ‘, or given as alist, e.g.'snr > 5 && frequency < 1000'or['snr > 5', 'frequency < 1000']
**kwargs
all other positional arguments are specific to the data format, see the online documentation for more details
table : EventTable
a table of events recovered from the remote database
Notes
The available named formats are:
Format |
Basic usage |
|---|---|
gravityspy |
|
hacr |
|
Examples
>>> from gwpy.table import EventTable
To download a table of all blip glitches from the Gravity Spy database:
>>> EventTable.fetch('gravityspy', 'glitches', selection='Label=Blip')
To download a table from any SQL-type server
>>> from sqlalchemy.engine import create_engine
>>> engine = create_engine(...)
>>> EventTable.fetch(engine, 'mytable')
fetch_open_data(catalog, columns=None, selection=None, host='https://www.gw-openscience.org', **kwargs)[source]Fetch events from an open-data catalogue hosted by GWOSC.
catalog : str
the name of the catalog to fetch, e.g.
'GWTC-1-confident'
columns : list of str, optional
the list of column names to read
selection : str, or list of str, optional
one or more column filters with which to downselect the returned events as they as read, e.g.
'mass1 < 30'; multiple selections should be connected by ‘ && ‘, or given as alist, e.g.'mchirp < 3 && distance < 500'or['mchirp < 3', 'distance < 500']
host : str, optional
the open-data host to use
filter(self, *column_filters)[source]Apply one or more column slice filters to this EventTable
Multiple column filters can be given, and will be applied concurrently
a column slice filter definition, e.g.
'snr > 10, or a filter tuple definition, e.g.('snr', <my_func>, <arg>)
table : EventTable
a new table with only those rows matching the filters
Notes
See Filtering tables for more details on using filter tuples
Examples
To filter an existing EventTable (table) to include only
rows with snr greater than 10, and frequency less than
1000:
>>> table.filter('snr>10', 'frequency<1000')
Custom operations can be defined using filter tuple definitions:
>>> from gwpy.table.filters import in_segmentlist
>>> filter(my_table, ('time', in_segmentlist, segs))
get_column(self, name)[source]Return the Column with the given name
This method is provided only for compatibility with the
ligo.lw.table.Table.
name : str
the name of the column to return
astropy.table.ColumnKeyError
if no column is found with the given name
hist(self, column, **kwargs)[source]Generate a HistogramPlot of this Table.
column : str
Name of the column over which to histogram data
method : str, optional
Name of
Axesmethod to use to plot the histogram, default:'hist'.
**kwargs
Any other keyword arguments, see below.
plot : Plot
The newly created figure.
See also
matplotlib.pyplot.figurefor documentation of keyword arguments used to create the figure.
matplotlib.figure.Figure.add_subplotfor documentation of keyword arguments used to create the axes.
gwpy.plot.Axes.histfor documentation of keyword arguments used to display the histogram, if the method keyword is given, this method might not actually be the one used.
plot(self, *args, **kwargs)[source]DEPRECATED, use EventTable.scatter
read(source, *args, **kwargs)[source]Read data into an EventTable
*args
other positional arguments will be passed directly to the underlying reader method for the given format
format : str, optional
the format of the given source files; if not given, an attempt will be made to automatically identify the format
columns : list of str, optional
the list of column names to read
selection : str, or list of str, optional
one or more column filters with which to downselect the returned table rows as they as read, e.g.
'snr > 5'; multiple selections should be connected by ‘ && ‘, or given as alist, e.g.'snr > 5 && frequency < 1000'or['snr > 5', 'frequency < 1000']
nproc : int, optional, default: 1
number of CPUs to use for parallel reading of multiple files
verbose : bool, optional
print a progress bar showing read status, default:
False
.. note::
Keyword arguments other than those listed here may be required depending on the
format
EventTableastropy.io.registry.IORegistryError
if the
formatcannot be automatically identified
IndexError
if
sourceis an empty list
Notes
The available built-in formats are:
Format |
Read |
Write |
Auto-identify |
Deprecated |
|---|---|---|---|---|
ascii |
Yes |
Yes |
No |
|
ascii.aastex |
Yes |
Yes |
No |
|
ascii.basic |
Yes |
Yes |
No |
|
ascii.cds |
Yes |
No |
No |
|
ascii.commented_header |
Yes |
Yes |
No |
|
ascii.csv |
Yes |
Yes |
Yes |
|
ascii.cwb |
Yes |
No |
No |
|
ascii.daophot |
Yes |
No |
No |
|
ascii.ecsv |
Yes |
Yes |
Yes |
|
ascii.fast_basic |
Yes |
Yes |
No |
|
ascii.fast_commented_header |
Yes |
Yes |
No |
|
ascii.fast_csv |
Yes |
Yes |
No |
|
ascii.fast_no_header |
Yes |
Yes |
No |
|
ascii.fast_rdb |
Yes |
Yes |
No |
|
ascii.fast_tab |
Yes |
Yes |
No |
|
ascii.fixed_width |
Yes |
Yes |
No |
|
ascii.fixed_width_no_header |
Yes |
Yes |
No |
|
ascii.fixed_width_two_line |
Yes |
Yes |
No |
|
ascii.html |
Yes |
Yes |
Yes |
|
ascii.ipac |
Yes |
Yes |
No |
|
ascii.latex |
Yes |
Yes |
Yes |
|
ascii.no_header |
Yes |
Yes |
No |
|
ascii.omega |
Yes |
No |
No |
|
ascii.rdb |
Yes |
Yes |
Yes |
|
ascii.rst |
Yes |
Yes |
No |
|
ascii.sextractor |
Yes |
No |
No |
|
ascii.tab |
Yes |
Yes |
No |
|
asdf |
Yes |
Yes |
Yes |
|
fits |
Yes |
Yes |
Yes |
|
gwf |
Yes |
Yes |
Yes |
|
hdf5 |
Yes |
Yes |
Yes |
|
hdf5.pycbc_live |
Yes |
No |
Yes |
|
hdf5.snax |
Yes |
No |
No |
|
ligolw |
Yes |
Yes |
Yes |
|
pandas.csv |
Yes |
Yes |
No |
|
pandas.fwf |
Yes |
No |
No |
|
pandas.html |
Yes |
Yes |
No |
|
pandas.json |
Yes |
Yes |
No |
|
root |
Yes |
Yes |
Yes |
|
root.cwb |
Yes |
No |
No |
|
root.omicron |
Yes |
No |
No |
|
votable |
Yes |
Yes |
Yes |
|
aastex |
Yes |
Yes |
No |
Yes |
cds |
Yes |
No |
No |
Yes |
csv |
Yes |
Yes |
No |
Yes |
daophot |
Yes |
No |
No |
Yes |
html |
Yes |
Yes |
No |
Yes |
ipac |
Yes |
Yes |
No |
Yes |
latex |
Yes |
Yes |
No |
Yes |
rdb |
Yes |
Yes |
No |
Yes |
Deprecated format names like aastex will be removed in a future version. Use the full
name (e.g. ascii.aastex) instead.
scatter(self, x, y, **kwargs)[source]Make a scatter plot of column x vs column y.
x : str
name of column defining centre point on the X-axis
y : str
name of column defining centre point on the Y-axis
color : str, optional, default:None
name of column by which to color markers
**kwargs
any other keyword arguments, see below
plot : Plot
the newly created figure
See also
matplotlib.pyplot.figurefor documentation of keyword arguments used to create the figure
matplotlib.figure.Figure.add_subplotfor documentation of keyword arguments used to create the axes
gwpy.plot.Axes.scatterfor documentation of keyword arguments used to display the table
tile(self, x, y, w, h, **kwargs)[source]Make a tile plot of this table.
x : str
name of column defining anchor point on the X-axis
y : str
name of column defining anchor point on the Y-axis
w : str
name of column defining extent on the X-axis (width)
h : str
name of column defining extent on the Y-axis (height)
color : str, optional, default:None
name of column by which to color markers
**kwargs
any other keyword arguments, see below
plot : Plot
the newly created figure
See also
matplotlib.pyplot.figurefor documentation of keyword arguments used to create the figure
matplotlib.figure.Figure.add_subplotfor documentation of keyword arguments used to create the axes
gwpy.plot.Axes.tilefor documentation of keyword arguments used to display the table
write(self, target, *args, **kwargs)[source]Write this table to a file
target: `str`
filename for output data file
*args
other positional arguments will be passed directly to the underlying writer method for the given format
format : str, optional
format for output data; if not given, an attempt will be made to automatically identify the format based on the
targetfilename
**kwargs
other keyword arguments will be passed directly to the underlying writer method for the given format
astropy.io.registry.IORegistryError
if the
formatcannot be automatically identified
Notes
The available built-in formats are:
Format |
Read |
Write |
Auto-identify |
Deprecated |
|---|---|---|---|---|
ascii |
Yes |
Yes |
No |
|
ascii.aastex |
Yes |
Yes |
No |
|
ascii.basic |
Yes |
Yes |
No |
|
ascii.commented_header |
Yes |
Yes |
No |
|
ascii.csv |
Yes |
Yes |
Yes |
|
ascii.ecsv |
Yes |
Yes |
Yes |
|
ascii.fast_basic |
Yes |
Yes |
No |
|
ascii.fast_commented_header |
Yes |
Yes |
No |
|
ascii.fast_csv |
Yes |
Yes |
No |
|
ascii.fast_no_header |
Yes |
Yes |
No |
|
ascii.fast_rdb |
Yes |
Yes |
No |
|
ascii.fast_tab |
Yes |
Yes |
No |
|
ascii.fixed_width |
Yes |
Yes |
No |
|
ascii.fixed_width_no_header |
Yes |
Yes |
No |
|
ascii.fixed_width_two_line |
Yes |
Yes |
No |
|
ascii.html |
Yes |
Yes |
Yes |
|
ascii.ipac |
Yes |
Yes |
No |
|
ascii.latex |
Yes |
Yes |
Yes |
|
ascii.no_header |
Yes |
Yes |
No |
|
ascii.rdb |
Yes |
Yes |
Yes |
|
ascii.rst |
Yes |
Yes |
No |
|
ascii.tab |
Yes |
Yes |
No |
|
asdf |
Yes |
Yes |
Yes |
|
fits |
Yes |
Yes |
Yes |
|
gwf |
Yes |
Yes |
No |
|
hdf5 |
Yes |
Yes |
Yes |
|
jsviewer |
No |
Yes |
No |
|
ligolw |
Yes |
Yes |
Yes |
|
pandas.csv |
Yes |
Yes |
No |
|
pandas.html |
Yes |
Yes |
No |
|
pandas.json |
Yes |
Yes |
No |
|
root |
Yes |
Yes |
Yes |
|
votable |
Yes |
Yes |
Yes |
|
aastex |
Yes |
Yes |
No |
Yes |
csv |
Yes |
Yes |
No |
Yes |
html |
Yes |
Yes |
No |
Yes |
ipac |
Yes |
Yes |
No |
Yes |
latex |
Yes |
Yes |
No |
Yes |
rdb |
Yes |
Yes |
No |
Yes |
Deprecated format names like aastex will be removed in a future version. Use the full
name (e.g. ascii.aastex) instead.