I/O¶
Read¶
Reading a generic fits file¶
Example:
>>> import nicerlab as ni
>>> filename = 'data_cl.evt'
>>> table, keys = ni.io.read_from_fits(
... filename, ext='EVENTS', cols=['TIME', 'PI'],
... keys=['TSTART', 'TSTOP', 'OBJECT'],
... as_table=True)
>>> keys
{'TSTART': 523327317.6109142, 'TSTOP': 523345136.3998488, 'OBJECT': 'TOO'}
>>> table
array([[ 5.23327318e+08, 6.11000000e+02],
[ 5.23327319e+08, 6.23000000e+02],
[ 5.23327320e+08, 3.02000000e+02],
...,
[ 5.23345135e+08, 5.99000000e+02],
[ 5.23345136e+08, 2.89000000e+02],
[ 5.23345136e+08, 2.83000000e+02]])
Alternatively we could have also just used astropy as:
>>> from astropy.table import Table
>>> tb = Table.read(filename, format='fits', hdu=1)['TIME', 'PI']
>>> tb
<Table length=5946>
TIME PI
float64 int32
------------- -----
523327317.829 611
523327319.446 623
523327320.199 302
... ...
523345135.417 599
523345135.787 289
523345136.275 283
>>> keys = {k: tb.meta[k] for k in ['TSTART', 'TSTOP', 'OBJECT']}
>>> keys
{'TSTART': 523327317.6109142, 'TSTOP': 523345136.3998488, 'OBJECT': 'TOO'}
However, this will load all columns from the fits table into memory, which is
sometimes unwieldy. In any case the read_from_fits() function is just a
building block used to construct a set of higher level convience functions, and
should seldomly be used directly.
Reading event data¶
Events only¶
If only the event arrival times are of interest these can be obtained by invoking the fits interface as:
>>> table = ni.io.read_from_fits(filename, ext='EVENTS', cols=['TIME'])
However, the table will be a 2-dimensional numpy array with only one defined
column, hence:
>>> events = table[:,0]
What’s more, we will actually want to construct an Event list object with the proper attributes set. To that end a convience function has been implemented that does all this for you:
>>> evt = ni.io.read_events(filename)
>>> evt.info()
Eventlist:
> counts......: 5946
> exposure....: 17818.788934648037 seconds
> start/stop..: 523327317.6109142 / 523345136.3998488
> MJD.........: 57967.02988188558
Events and ...¶
For convience a number of combination functions are implemented that read event arrival times and some other datum from the fits table:
>>> evt, gti = ni.io.read_events_and_gti(filename)
>>> gti
array([[ 5.23327318e+08, 5.23329114e+08],
[ 5.23333245e+08, 5.23334856e+08],
[ 5.23338946e+08, 5.23340281e+08],
[ 5.23344887e+08, 5.23345136e+08]])
>>>
>>> tb = ni.io.read_events_and_pi(filename)
>>> tb
array([[ 5.23327318e+08, 6.11000000e+02],
[ 5.23327319e+08, 6.23000000e+02],
[ 5.23327320e+08, 3.02000000e+02],
...,
[ 5.23345135e+08, 5.99000000e+02],
[ 5.23345136e+08, 2.89000000e+02],
[ 5.23345136e+08, 2.83000000e+02]])
Reading good time intervals¶
You can also read the GTI table only:
>>> table = ni.io.read_from_fits(filename, ext='GTI', cols=['START', 'STOP'])
which has its own convience function:
>>> gti = ni.io.read_gti(filename)
>>> gti
array([[ 5.23327318e+08, 5.23329114e+08],
[ 5.23333245e+08, 5.23334856e+08],
[ 5.23338946e+08, 5.23340281e+08],
[ 5.23344887e+08, 5.23345136e+08]])
Write¶
Write power spectrum¶
Write a single Power density spectrum object to a fits file
ni.io.write_pds(pds, "pds.fits")
If the pds has multiple rows, then this works too.