Data Structures

Event list

An Eventlist represents a list of photon arrival times. This object is a ndarray subclass with the following added attributes:

tstart	The start time of the observation
tstop	The stop time of the observation
MJD	The observation start time in MJD

If a tstart or tstop time is not explicitly defined, the respective smallest and largest value in the array of arrival times will be used instead. The MJD of an Eventlist is zero unless explicitly defined.

Because an Eventlist is just an ndarray standard numpy methods can be used to manipulate the data. Consider the following example where we generate some random data and proceed to sort the Eventlist on time:

>>> import numpy as np
>>> import nicerlab as ni
>>> data = np.random.uniform(10,20,500)
>>> evt = ni.Eventlist(data, tstart=10, tstop=20)
>>> evt = np.sort(evt)
>>> evt.info()
Eventlist:
> counts......: 500
> exposure....: 10 seconds
> start/stop..: 10 / 20
> MJD.........: 0

Note

Event list data should generally be time ordered, however, this is not a strict requirement for nicerlab. Data contained in an Eventlist object is allowed to be out-of-order, and routines operating on an Eventlist will return the correct ouput either way.

Light curve

A Lightcurve object is an array of event counts in equidistant time bins. This object is a ndarray subclass with the following added attributes:

dt	Time bin width in seconds
tstart	The start time of the observation
tstop	The stop time of the observation
MJD	The observation start time in MJD

The bin width will default to 1 if no value is provided. Like for the Eventlist, if the tstart or tstop time is not explicitly defined, the respective smallest and largest value in the array of arrival times will be used instead. The MJD of an Eventlist is zero unless explicitly defined.

In addition to the extra attributes, the Lightcurve object also has special member functions:

timespace	Generate an array of times
mjdspace	Generate an array of MJD times

A Lightcurve can be constructed manually from any iterable list of counts as:

>>> from nicerlab.lightcurve import Lightcurve
>>> counts = [11, 12, 10, 8, 15, 12]
>>> lc = Lightcurve(counts, dt=2, tstart=0, mjd=55750)
>>> lc
Lightcurve([11, 12, 10, 8, 15, 12])
>>> lc.timespace()
array([ 0., 2., 4., 6., 8.])
>>> np.sum(lc.reshape(-1,2), axis=1)
Lightcurve([23, 18, 27])

Warning

The Lightcurve constructor will not check if the combination dt/tstart/tstop are self consistent. The array-size/bin-width always take precedence in determining the time axis of the light curve.

An example:

>>> import numpy as np
>>> import nicerlab as ni
>>> import matplotlib.pyplot as plt
>>> data = np.sort(np.random.uniform(0,12,500))
>>> evt = ni.Eventlist(data, tstart=0, tstop=12)
>>> lc = ni.make_light_curve(evt, dt=0.25) / 0.25
>>> plt.plot(lc.timespace(), lc);
>>> plt.xlabel('MET (s)');
>>> plt.ylabel('count-rate (ct/s)');
>>> plt.show()

Power density spectrum

A Powerspectrum object is an array of powers densities. Note that the object does not care about what normalization is used. By default the make_power_spectrum() will use the Leahy normalization. The following attributes have been added to the object

df	Frequency bin width in Hertz
tstart	The start time of the observation
tstop	The stop time of the observation
MJD	The observation start time in MJD
stack	The number of FFT segments in the spectrum

Additionally it has a special member function

freqspace

Generate an array of frequencies

Spectrum

A spectrum is an PI spectrum object.