BATSE Catalogs (gdt.missions.cgro.batse.catalogs)¶
The HEASARC hosts several BATSE catalogs, including a Trigger Catalog that contains information about every BATSE trigger, a Burst Catalog that contains standard analysis of every triggered GRB, and spectroscopy catalogs. HEASARC provides a way to search these catalogs online through their Browse interface, but we offer a way to do it in Python through the Data Tools.
Let’s look at the trigger catalog first:
>>> from gdt.missions.cgro.batse.catalogs import BatseTriggerCatalog
>>> trigcat = BatseTriggerCatalog()
Sending request and awaiting response from HEASARC...
Downloading batsetrigs from HEASARC via w3query.pl...
Finished in 4 s
>>> trigcat
<BatseTriggerCatalog: 9 columns, 5372 rows>
Depending on your connection, initialization may take a few seconds. You can see what columns are available in the catalog:
>>> print(trigcat.columns)
('OBSID', 'TRIGGER_ID', 'START_TIME', 'STOP_TIME', 'RA', 'DEC', 'TRIG_TYPE',
'BII', 'LII')
You can also return the range of values for a given column:
>>> trigcat.column_range('TRIGGER_ID')
('00105', '08088')
If you only care about specific columns in the table, you can return a numpy record array with only those columns. Let’s return a table with the trigger name and time for every trigger:
>>> trigcat.get_table(columns=('TRIGGER_ID', 'START_TIME'))
rec.array([('00105', '48367.3847801'),
('00114', '48373.3787384'),
('00160', '48383.6050579'), ...,
('03934', ' 50058.363285'),
('06985', ' 51035.774646'),
('06986', ' 51036.281345')],
dtype=[('TRIGGER_ID', '<U5'), ('START_TIME', '<U13')])
Importantly, we can make slices of the catalog based on conditionals. Let’s only select triggers with positive declinations:
>>> sliced_trigcat = trigcat.slice('DEC', lo=0.0, hi=90.0)
>>> sliced_trigcat
<BatseTriggerCatalog: 9 columns, 1870 rows>
>>> sliced_trigcat.get_table(columns=('TRIGGER_ID', 'RA', 'DEC'))
rec.array([('00105', 269.3 , 26.5 ),
('00171', 340.2 , 39.6 ),
('00179', 266.5 , 57.2 ), ...,
('02580', 301.862, 11.093),
('06985', 349.934, 24.645),
('06986', 266.796, 3.509)],
dtype=[('TRIGGER_ID', '<U5'), ('RA', '<f8'), ('DEC', '<f8')])
You can also slice on multiple conditionals, simultaneously. Select everything that has a positive declination and a is classified as a ‘burst’:
>>> sliced_trigcat2 = trigcat.slices([('DEC', 0.0, 90.0),
>>> ('TRIG_TYPE', 'burst', 'burst')])
>>> sliced_trigcat2
<BatseTriggerCatalog: 9 columns, 1254 rows>
>>> sliced_trigcat2.get_table(columns=('trigger_name', 'trigger_time', 'error_radius'))
rec.array([('00105', 'burst ', 269.3 , 26.5 ),
('00171', 'burst ', 340.2 , 39.6 ),
('00179', 'burst ', 266.5 , 57.2 ), ...,
('02580', 'burst ', 301.862, 11.093),
('06985', 'burst ', 349.934, 24.645),
('06986', 'burst ', 266.796, 3.509)],
dtype=[('TRIGGER_ID', '<U5'), ('TRIG_TYPE', '<U11'), ('RA', '<f8'), ('DEC', '<f8')])
You’ll notice in the table listing that there are multiple datatypes.
We can connect to the other catalogs in the same way. For example, here is the spectral catalog:
>>> from gdt.missions.cgro.batse.catalogs import BatseSpectralCatalog
>>> spec_cat = BatseSpectralCatalog()
Sending request and awaiting response from HEASARC...
Downloading bat5bgrbsp from HEASARC via w3query.pl...
Finished in 21 s
>>> spec_at
<BatseSpectralCatalog: 185 columns, 2145 rows>
Again, this may take several seconds, largely because of how the HEASARC perl API works.
For more information on working with catalogs, see The BrowseCatalog Class.
Reference/API¶
gdt.missions.cgro.batse.catalogs Module¶
Classes¶
|
The BATSE GRB trigger Catalog. |
|
The BATSE 4B catalog of localizations and durations. |
|
The BATSE 5B spectral catalog. |
|
The BATSE time-resolved spectral catalog of bright GRBs. |
|
The BATSE Earth Occultation Catalog of Low-Energy Gamma-ray Sources. |
|
The BATSE Pulsar Observations Catalog. |
|
The BATSE Trigger Catalog. |
Class Inheritance Diagram¶
